Rejected Article tracker#

This Python notebook shows how publishers can use the Dimensions Analytics API to identify whether articles they chose not to publish were published somewhere else, and if so who, when and with what citation metrics.

In this notebook we will:

Import a .csv file of required fields for a list of rejected articles
Leverage the Dimensions API’s full-text, fuzzy search capabilities to iteratively search the Dimensions API for publications like the rejected articles.
Join the rejected articles with the best-matching search results
Measure the strength of the matches and provide ideas for validation before proceeding to detailed analyses.

Note this notebook can be run either using Google Colab or standard Jupyter.

[1]:

import datetime
print("==\nCHANGELOG\nThis notebook was last run on %s\n==" % datetime.date.today().strftime('%b %d, %Y'))

==
CHANGELOG
This notebook was last run on Mar 03, 2025
==

Prerequisites#

This notebook assumes you have installed the Dimcli library and are familiar with the ‘Getting Started’ tutorial.

[2]:

!pip install dimcli nltk pandasql python-Levenshtein openpyxl -U --quiet

import dimcli
from dimcli.utils import *

import io
import json
import os
import sys
import time
import pandas as pd
import numpy as np
from pandasql import sqldf
import pandasql as ps
if 'google.colab' in sys.modules:
  from google.colab import files
#
pd.set_option('display.max_columns', None)


print("==\nLogging in..")
# https://digital-science.github.io/dimcli/getting-started.html#authentication
ENDPOINT = "https://app.dimensions.ai"
if 'google.colab' in sys.modules:
  import getpass
  KEY = getpass.getpass(prompt='API Key: ')
  dimcli.login(key=KEY, endpoint=ENDPOINT)
else:
  KEY = ""
  dimcli.login(key=KEY, endpoint=ENDPOINT)
dsl = dimcli.Dsl()

==
Logging in..
API Key: ··········
Dimcli - Dimensions API Client (v1.4)
Connected to: <https://app.dimensions.ai/api/dsl> - DSL v2.10
Method: manual login

1. Load Data on Rejected Articles#

For this tutorial, we are using a small sample file of made-up rejected articles, rejected-articles-sample-data.csv. If you run this notebook in Jupyter, the sample file is loaded automatically; in Google Colab you will be prompted to upload your own Excel or .csv file instead.

This list of fields with these specific, case-sensitive field names are required:

Manuscript ID: a unique identifier that will tie your search results back to a particular rejected article
Date of Rejection: Date the article was rejected
Title: The title of the rejected article
Keywords: Comma-separated keywords describing the rejected article (if these aren’t available you can build them from the Title field - see the optional keyword-extraction snippet in section 2 below).
First Author: the First Author as Last, First (only Last will be used)
Corr Author: the Corresponding Author as Last, First (only Last will be used)

Any additional fields in your file, regardless of name, will propagate through the query unchanged and remain available for subsequent analytics. Some examples of fields you might wish to include: journal submitted to, editor’s name, reviewer’s name, submission date, reject reason or the like.

The import cell below handles both Excel and .csv files.

[6]:

if 'google.colab' in sys.modules:
    # In Colab: upload your own Excel or .csv file of rejected articles
    uploaded = files.upload()
    file_name = list(uploaded.keys())[0]  # Get the uploaded file name
    if file_name.lower().endswith(('.xlsx', '.xls')):
        RejectedArticles = pd.read_excel(io.BytesIO(uploaded[file_name]), engine='openpyxl')
    else:
        RejectedArticles = pd.read_csv(io.BytesIO(uploaded[file_name]), encoding='latin1')
else:
    # In Jupyter: load the sample data shipped with this notebook.
    # Point this at your own file (pd.read_excel for Excel) to use real data.
    SAMPLE = "rejected-articles-sample-data.csv"
    SAMPLE_URL = ("https://raw.githubusercontent.com/digital-science/dimensions-api-lab/"
                  "master/cookbooks/2-publications/rejected-articles-sample-data.csv")
    RejectedArticles = pd.read_csv(
        SAMPLE if os.path.exists(SAMPLE) else SAMPLE_URL, encoding='latin1')

if 'Date of Rejection' in RejectedArticles:
    RejectedArticles['Date of Rejection'] = pd.to_datetime(
        RejectedArticles['Date of Rejection'], errors='coerce'
    ).dt.strftime('%Y-%m-%d')

RejectedArticles.head(3)

[6]:

  Manuscript ID Date of Rejection Reject Reason  \
0      JSS76145        2001-04-01   Reject Open
1      JSS50060        2012-06-23   Reject Open
2      JSS48881        1998-01-01      EDREJECT

                                               Title    First Author  \
0  Erythrodiol-3-acetate, pentacyclic triterpenoi...  Moon, Hyung-In
1  A Programmable Dual-RNA-Guided DNA Endonucleas...   Jinek, Martin
2  Ileal-lymphoid-nodular hyperplasia, non-specif...   Wakefield, AJ

     Corr Author                                         Co-Authors  \
0  Chung, Jin Ho  Moon, Hyung-In; Seo, Dong Wan; Kim, Kyu-Han; C...
1     Fonfara, I  Jinek, Martin; Chylinski, Krzysztof; Fonfara, ...
2  Wakefield, AJ  Wakefield, AJ; Murch, SH; Anthony, A; Linnell,...

   Subject Category        Editor     Submitted Journal  Article Type  \
0               NaN  Kim, Soo-jin        Science Serial           NaN
1               NaN  Garcia, Luis        Science Serial           NaN
2               NaN  Patel, Priya  Chemistry Compendium           NaN

                                            Keywords  Custom  Funders
0  Humans, Enzyme Inhibitors/isolation & purifica...     NaN      NaN
1  Deoxyribonucleases, Type II Site-Specific/meta...     NaN      NaN
2  Developmental Disabilities/etiology*, Child, H...     NaN      NaN

2. Clean input file to prepare datapoints to work with DSL#

[7]:

import string

RejArt = RejectedArticles
"""
#Optional: If your input data does not contain a field for "Keywords" you can make one based on the
#          important words in your title with this section.

import nltk
from nltk.corpus import stopwords
nltk.download('stopwords')
stop_words = set(stopwords.words('english'))
def extract_keywords(title):
    return ', '.join([word.capitalize() for word in title.split() if word.lower() not in stop_words])
RejArt['Keywords'] = RejArt['Title'].apply(extract_keywords)
RejArt.head(6)
"""

cols = RejArt.select_dtypes(['object']).columns
RejArt[cols] = RejArt[cols].apply(lambda x: x.str.strip())

RejArt['Keywords_Or'] = RejArt['Keywords'].str.replace(',', 'abcdefghijkl')
RejArt['Keywords_Or'] = RejArt['Keywords_Or'].str.replace('abcdefghijkl', ' OR ')
RejArt['Keywords_Or'] = RejArt['Keywords_Or'].str.replace(' and ', ' OR ')
RejArt['Keywords_Or'] = RejArt['Keywords_Or'].str.replace(r'\b(OR\s+OR)+\b', ' OR ', regex=True)
RejArt['Keywords_Or'] = RejArt['Keywords_Or'].str.replace(r'\s+', ' ', regex=True).str.strip()  # Remove extra spaces

RejArt['Keywords_And'] = RejArt['Keywords_Or'].str.replace(r'\bOR\b', 'AND', regex=True)
RejArt['Keywords_And'] = RejArt['Keywords_And'].str.replace(r'\b(AND\s+AND)+\b', ' AND ', regex=True)

#Remove punctuation (punctuation can cause errors in the DSL query):
RejArt[['Keywords_Or', 'Keywords_And', 'Title']] = RejArt[['Keywords_Or', 'Keywords_And', 'Title']].apply(
    lambda x: x.str.translate(str.maketrans(string.punctuation, ' ' * len(string.punctuation))))
RejArt['FALast'] = RejArt['First Author'].str.split(',').str[0]
RejArt['CALast'] = RejArt['Corr Author'].str.split(',').str[0]

RejArt = RejArt[['FALast','CALast','Keywords_Or','Keywords_And','Article Type','Title','Date of Rejection','Manuscript ID']]
print(len(RejArt))
RejArt.head(3)

[7]:

	FALast	CALast	Keywords_Or	Keywords_And	Article Type	Title	Date of Rejection	Manuscript ID
0	Moon	Chung	Humans OR Enzyme Inhibitors isolation purifi...	Humans AND Enzyme Inhibitors isolation purif...	NaN	Erythrodiol 3 acetate pentacyclic triterpenoi...	2001-04-01	JSS76145
1	Jinek	Fonfara	Deoxyribonucleases OR Type II Site Specific me...	Deoxyribonucleases AND Type II Site Specific m...	NaN	A Programmable Dual RNA Guided DNA Endonucleas...	2012-06-23	JSS50060
2	Wakefield	Wakefield	Developmental Disabilities etiology OR Child ...	Developmental Disabilities etiology AND Child...	NaN	Ileal lymphoid nodular hyperplasia non specif...	1998-01-01	JSS48881

3. Iteratively Query the Dimensions API for each row of the RejectedArticles sheet.#

This section iteratively populates and executes an API call (example below) for each row in the RejArt dataframe.

This leverages Dimensions’ full-text, fuzzy search to search the Publications dataset for the Rejected Title or Keywords.
Results are limited to articles that were published after the rejected date by both the first and corresponding authors together.
Since the fuzzy search will result in multiple possible matches, we keep only the most relevant match for each searched row. Finding the exact title phrase will earn a higher score than finding a match for just the keywords; the score also factors in where the terms are found - matches in the abstract or title fields will get higher scores than matches in the body of the publication.
The results of the calls are accumulated in a single dataframe and tagged with the ManuscriptID associated with the search values.

Query Example: search publications for “Microtubule-dependent and independent roles of spastin in lipid droplet dispersion and biogenesis” or for “(Cytoskeleton AND Membrane AND lipid biology AND Disease AND Metabolism AND In vitro AND Rodent)” where ((authors = “Tadepalle” and authors = “Rugarli” and date_print > “2020-03-24”) or (authors = “Tadepalle” and authors = “Rugarli” and date_print is empty)) and type = “article” return publications[id+authors+authors_count+title+date_print+journal+times_cited+altmetric+recent_citations+field_citation_ratio+relative_citation_ratio+score] sort by score limit 1

[8]:

#RejArt = RejArt.head(10)  ##For Testing, limit the dataset to a few records- comment this line out to analyze the entire input file

TitlesFoundRaw = pd.DataFrame()
RejArtRecCount= len(RejArt)
RunTime = "{:.2f}".format(RejArtRecCount * 5 / 60)
LoopNo = 0
print("This should take approximately ",RunTime," minutes to complete.")

query_template = """
search publications
for "{}"
or for "({})"
where ((authors = "{}" and authors = "{}" and date_print > "{}") or (authors = "{}" and authors = "{}" and date_print is empty))
and type = "article"
return publications[id+authors+authors_count+title+date_print+journal+publisher+
                    times_cited+altmetric+recent_citations+field_citation_ratio+
                    relative_citation_ratio+score]
sort by score limit 1
"""
for index, row in RejArt.iterrows():
    First_Author = row['FALast']
    Corr_Author = row['CALast']
    Keywords = row['Keywords_And']
    Title = dsl_escape(row['Title'], True)
    RejDate = row['Date of Rejection']
    ManuscriptID = row['Manuscript ID']
    LoopNo = (LoopNo + 1)
    data = pd.DataFrame()
    print("*****Loop ",LoopNo," of ",RejArtRecCount, Title, Keywords, First_Author, Corr_Author, RejDate, "***************************************")
    try:
        q = query_template.format(Title, Keywords, First_Author, Corr_Author, RejDate,First_Author, Corr_Author)
        #print(q)
        data = dsl.query(q).as_dataframe()
        data['Reject_ManID'] = ManuscriptID
    except Exception as e:
        # Handle the error by creating the 'data' DataFrame with the 'Reject_ManID' and error flag
        data = pd.DataFrame({'Reject_ManID': [ManuscriptID], 'id': ['error']})
    TitlesFoundRaw = pd.concat([TitlesFoundRaw, data])
    time.sleep(.33)  # Seconds
#print(q)
TitlesFoundRaw.assign(authors='Suppressed/Abridged').head(1)

This should take approximately  1.42  minutes to complete.
*****Loop  1  of  17 Erythrodiol 3 acetate  pentacyclic triterpenoid from Styrax japonica  expressions of matrix metalloproteinase in cultured human fibroblasts Humans AND Enzyme Inhibitors isolation   purification AND Skin cytology AND Gene Expression Regulation AND Enzymologic physiology AND Skin enzymology AND Acetates chemistry AND Triterpenes chemistry AND Triterpenes isolation   purification AND Acetates isolation   purification AND Styrax  AND Cells AND Cultured AND Fibroblasts drug effects AND Plant Extracts isolation   purification AND Oleanolic Acid analogs   derivatives  AND Male AND Enzyme Inhibitors pharmacology AND Matrix Metalloproteinase 1 biosynthesis  AND Fibroblasts enzymology  AND Skin drug effects AND Acetates pharmacology AND Child AND Preschool AND Child AND Gene Expression Regulation AND Enzymologic drug effects AND Matrix Metalloproteinase Inhibitors AND Oleanolic Acid pharmacology  AND Triterpenes pharmacology  AND Matrix Metalloproteinase 2 biosynthesis  AND Oleanolic Acid chemistry AND Plant Extracts chemistry AND Plant Stems AND Oleanolic Acid isolation   purification AND Enzyme Inhibitors chemistry AND Plant Extracts pharmacology Moon Chung 2001-04-01 ***************************************
Returned Publications: 1 (total = 6)
Time: 3.98s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  2  of  17 A Programmable Dual RNA Guided DNA Endonuclease in Adaptive Bacterial Immune Deoxyribonucleases AND Type II Site Specific metabolism  AND Deoxyribonucleases AND Type II Site Specific genetics AND Inverted Repeat Sequences  AND Streptococcus pyogenes enzymology  AND Plasmids metabolism AND Deoxyribonucleases AND Type II Site Specific chemistry AND DNA Breaks AND Double Stranded  AND Molecular Sequence Data AND RNA metabolism  AND Streptococcus pyogenes physiology AND Nucleic Acid Conformation AND Base Sequence AND Bacteriophages immunology  AND DNA Cleavage  AND RNA chemistry Jinek Fonfara 2012-06-23 ***************************************
Returned Publications: 1 (total = 1)
Time: 1.77s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  3  of  17 Ileal lymphoid nodular hyperplasia  non specific colitis and pervasive developmental disease in children Developmental Disabilities etiology  AND Child AND Humans AND Vaccines AND Combined adverse effects AND Male AND Mumps Vaccine adverse effects  AND Child AND Preschool AND Hyperplasia pathology AND Lymphoid Tissue pathology  AND Female AND Measles complications AND Measles Mumps Rubella Vaccine AND Otitis Media complications AND Ileum pathology  AND Rubella Vaccine adverse effects  AND Measles Vaccine adverse effects  AND Enterocolitis etiology  Wakefield Wakefield 1998-01-01 ***************************************
Returned Publications: 1 (total = 19)
Time: 1.73s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  4  of  17 Suppression of RNA Recognition by Toll like Receptors  The Impact of Nucleoside Modification and the Evolutionary Origin of RNA Dendritic Cells metabolism AND Signal Transduction physiology  AND Toll Like Receptor 7 AND Humans AND Toll Like Receptor 3 AND Signal Transduction genetics AND Nucleosides metabolism  AND Toll Like Receptor 8 AND RNA antagonists   inhibitors AND Immunoglobulins immunology AND Cytokines metabolism AND Biomarkers AND Receptors AND Cell Surface physiology  AND Evolution AND Molecular  AND Dendritic Cells drug effects AND HLA DR Antigens immunology AND Toll Like Receptors AND Dendritic Cells immunology AND CD83 Antigen AND Membrane Glycoproteins immunology AND Phosphatidylethanolamines pharmacology AND RNA metabolism  AND Antigens AND CD AND RNA genetics AND Cell Line AND Membrane Glycoproteins physiology  Kariko Weissman 2005-07-17 ***************************************
Returned Publications: 1 (total = 12)
Time: 4.85s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  5  of  17 Tracheobronchial transplantation with a stem cell seeded bioartificial nanocomposite  a proof of concept study Epoetin Alfa AND Male AND Recombinant Proteins therapeutic use AND Carcinoma AND Mucoepidermoid surgery AND Leukocytes AND Mononuclear metabolism AND Tissue Scaffolds  AND Bioreactors AND Blood Vessel Prosthesis AND Bone Marrow Transplantation AND Nanocomposites chemistry AND Neovascularization AND Physiologic AND Adult AND Leukocytes AND Mononuclear transplantation  AND Regeneration AND Bronchoscopy AND MicroRNAs metabolism AND Tracheal Neoplasms surgery  AND Cell Proliferation AND Polyethylene Terephthalates AND Erythropoietin therapeutic use AND Humans AND Transplantation AND Autologous AND Hematopoietic Stem Cells metabolism AND Tissue Engineering methods  AND Neoplasm Recurrence AND Local surgery AND Bronchial Neoplasms surgery  AND Flow Cytometry AND Granulocyte Colony Stimulating Factor therapeutic use Macchiarini Jungebluth 2009-10-07 ***************************************
Returned Publications: 1 (total = 12)
Time: 5.58s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  6  of  17 Superconductivity in molecular crystals induced by charged injections molecular crystals AND charge injection AND charge transfer salts Schön Batlogg 1990-06-10 ***************************************
Returned Publications: 1 (total = 1)
Time: 0.93s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  7  of  17 New Stellar Orbits around the Galactic Center Black Hole dark mass AND black hole AND young stars AND m telescope Ghez Ghez 2005-02-06 ***************************************
Returned Publications: 1 (total = 86)
Time: 4.01s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  8  of  17 The Forever Diamond  Contrast Reversals Along Thin Edges Create the Appearance of Objects in Motion luminous phase AND modulation AND temporal contrast AND thin edges Flynn Shapiro 2017-05-09 ***************************************
Returned Publications: 0
Time: 12.36s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  9  of  17 Potential Applications to Treat Cancer with Green Synthesis of Metallic Nanoparticles green synthesis AND nanoparticles AND biological entities AND metal nanoparticles Zhang Gu 2019-08-07 ***************************************
Returned Publications: 1 (total = 81)
Time: 0.41s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  10  of  17 Seasonal impact in admissions and burn profiles in a desert burn unit seasonal impact AND pavement burns AND desert climate Saquib Saquib 2020-06-01 ***************************************
Returned Publications: 1 (total = 3)
Time: 0.41s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  11  of  17 Immediate effects of treadmill walking in individuals with Lewy body dementia and Huntington’s disease Lewy Body Disease physiopathology  AND Pilot Projects AND Walking physiology  AND Humans AND Male AND Treatment Outcome AND Female AND Exercise Therapy  AND Huntington Disease physiopathology  AND Gait Disorders AND Neurologic therapy  AND Middle Aged AND Aged AND 80 AND over AND Feasibility Studies AND Aged Kegelmeyer Kloos 2017-08-08 ***************************************
Returned Publications: 1 (total = 1)
Time: 6.05s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  12  of  17 Overturned abusive head trauma and shaken baby syndrome convictions in the US  Prevalence  legal basis  and medical evidence Prevalence AND Child AND Retrospective Studies AND Craniocerebral Trauma etiology  AND Humans AND Craniocerebral Trauma diagnosis  AND United States epidemiology AND Shaken Baby Syndrome epidemiology  AND Child Abuse diagnosis  AND Craniocerebral Trauma epidemiology  AND Infant Narang Narang 2021-03-03 ***************************************
Returned Publications: 1 (total = 2)
Time: 5.93s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  13  of  17 Long COVID  major findings  mechanisms and recommendations Biomedical Research  AND Humans AND COVID 19 Testing AND Post Acute COVID 19 Syndrome AND COVID 19  AND Child AND SARS CoV 2 Davis Topol 2020-08-18 ***************************************
Returned Publications: 1 (total = 3)
Time: 0.41s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  14  of  17 Large language models identify functional protein sequences across diverse families Estrogens AND Conjugated  USP   AND Chorismate Mutase metabolism AND Language AND Proteins genetics  AND Amino Acid Sequence Madani Naik 2022-10-31 ***************************************
Returned Publications: 1 (total = 1)
Time: 1.59s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  15  of  17 antiSMASH 7 0  new and improved predictions for detection  regulation  chemical structures and visualisations  Bacteria genetics AND Archaea genetics AND Computers  AND Bacteria metabolism AND Multigene Family AND Genome AND Microbial AND Software  AND Secondary Metabolism genetics Blin nan 2023-02-25 ***************************************
Returned Publications: 0
Time: 1.74s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  16  of  17 Large language models in medicine Humans AND Technology AND Medicine  AND Software AND Artificial Intelligence  AND Language Thirunavukarasu Ting 2021-03-25 ***************************************
Returned Publications: 1 (total = 9)
Time: 5.61s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.
*****Loop  17  of  17 The impact of omidubicel on immune reconstitution and infections in cord blood transplant patients Transplantation AND Homologous adverse effects AND Fetal Blood AND Hematopoietic Stem Cell Transplantation adverse effects  AND Graft vs Host Disease etiology  AND Immune Reconstitution  AND Cord Blood Stem Cell Transplantation adverse effects  AND Humans De Gandhi 2023-07-06 ***************************************
Returned Publications: 1 (total = 1)
Time: 0.58s
WARNINGS [1]
Field current_organization_id of the authors field is deprecated and will be removed in the next major release.

[8]:

	id	title	altmetric	authors	authors_count	date_print	field_citation_ratio	publisher	recent_citations	relative_citation_ratio	score	times_cited	journal.id	journal.title	Reject_ManID
0	pub.1035176145	RETRACTED: Erythrodiol-3-acetate, pentacyclic ...	3.0	Suppressed/Abridged	6.0	2005-03	0.57	Elsevier	0.0	0.1	314.91736	6.0	jour.1089348	Journal of Ethnopharmacology	JSS76145

3a - Optional: Pull accepted articles and Union with Search Results#

By pulling the articles you did choose to publish, you can benchmark the metrics of rejected vs. published articles.

[10]:

# pull "accepted" publications by filtering the API call on Journal title, Publisher name or the like and returning the same fields as above
# May require FOR LOOPS to pull complete results

#AcceptedRaw = dsl.query_iterative(f"""
#search publications
#where publisher = "Springer Nature"
#and journal = "jour.1018957"
#and type = "article"
#and year > 2000
#return publications[id+authors+authors_count+title+date_print+journal+publisher+
#                    times_cited+altmetric+recent_citations+field_citation_ratio+
#                    relative_citation_ratio+score]""", verbose=True).as_dataframe()
#
#Flag as Accepted instead of using the Rejected ID:
#AcceptedRaw['Reject_ManID'] = "Accepted"

#Combine datasets:
#TitlesFoundRaw = pd.concat([TitlesFoundRaw, AcceptedRaw], ignore_index=True)
#print(len(TitlesFoundRaw))
#TitlesFoundRaw.head(3)

4. Identify first, last and corresponding author from the API results#

The authors field as returned from the API is repeated and nested and contains many fields that aren’t relevant to this analysis. We will build a streamlined dataframe to make it easier to compare the results with our search titles and authors.

[11]:

Authors_FLC = TitlesFoundRaw[['id','authors','authors_count']]
Authors_FLC = explode_nested_repeated_field(Authors_FLC, "authors")
Authors_FLC['AuthorNumber'] = Authors_FLC.groupby(['id']).cumcount()+1;
Authors_FLC['authors_count'] = Authors_FLC.groupby('id')['AuthorNumber'].transform('max')

Authors_FLC['authors_last_name'] = Authors_FLC['authors_last_name'].fillna('UnknownAuthor')
Authors_FLC['authors_corresponding'] = Authors_FLC['authors_corresponding'].fillna(False)

# Aggregate
Authors_FLC = Authors_FLC.groupby('id').agg(
    FirstAuthor=('authors_last_name', lambda x: ','.join(Authors_FLC.loc[x.index, 'authors_last_name'][Authors_FLC.loc[x.index, 'AuthorNumber'] == 1])),
    LastAuthor=('authors_last_name', lambda x: ','.join(Authors_FLC.loc[x.index, 'authors_last_name'][Authors_FLC.loc[x.index, 'AuthorNumber'] == Authors_FLC.loc[x.index, 'authors_count']])),
    CorrAuthor=('authors_last_name', lambda x: ','.join(Authors_FLC.loc[x.index, 'authors_last_name'][Authors_FLC.loc[x.index, 'authors_corresponding'] == True]))
).reset_index()

print(Authors_FLC)
Authors_FLC.head(7)

                id      FirstAuthor    LastAuthor   CorrAuthor
0   pub.1035176145             Moon         Chung   Moon,Chung
1   pub.1041850060            Jinek   Charpentier
2   pub.1046439810         Weinberg          Ghez
3   pub.1047248881        Wakefield  Walker-Smith    Wakefield
4   pub.1047376940           Karikó      Weissman       Karikó
5   pub.1049161136       Jungebluth   Macchiarini  Macchiarini
6   pub.1050062519            Schön       Batlogg      Batlogg
7   pub.1132135047            Zhang         Zhang        Zhang
8   pub.1134496487           Saquib    Chestovich       Saquib
9   pub.1136233657       Kegelmeyer         Kloos        Kloos
10  pub.1142388680           Narang        Pierce       Narang
11  pub.1154503709            Davis         Topol        Topol
12  pub.1154872323           Madani          Naik  Madani,Naik
13  pub.1160759555  Thirunavukarasu          Ting         Ting
14  pub.1169427057               De        Gandhi       Gandhi

[11]:

	id	FirstAuthor	LastAuthor	CorrAuthor
0	pub.1035176145	Moon	Chung	Moon,Chung
1	pub.1041850060	Jinek	Charpentier
2	pub.1046439810	Weinberg	Ghez
3	pub.1047248881	Wakefield	Walker-Smith	Wakefield
4	pub.1047376940	Karikó	Weissman	Karikó
5	pub.1049161136	Jungebluth	Macchiarini	Macchiarini
6	pub.1050062519	Schön	Batlogg	Batlogg

5. Create a Dataframe that places search terms and search results on the same row#

[12]:

#Replace authors field with Authors_FLC created in prior cell:
TitlesFound = TitlesFoundRaw.drop('authors', axis=1)
TitlesFound = pd.merge(
    left=TitlesFound,
    right=Authors_FLC,
    left_on=['id'],
    right_on=['id'],
    how='left'
)
TitlesFound.head(9)

#Add Prefixes to Dimensions API results and original input file for clarity:
TitlesFound = TitlesFound.add_prefix("Dim_")
RejArtJoiner = RejectedArticles.add_prefix("RA_")

#Join Dimensions results to original input file for comparison
Matched = pd.merge(
    left=RejArtJoiner,
    right=TitlesFound,
    left_on=['RA_Manuscript ID'],
    right_on=['Dim_Reject_ManID'],
    how='left'
)
#Identify created fields
Matched = Matched.rename({'RA_Keywords_And':'Input_Keywords_And','RA_CALast':'Input_CALast','RA_FALast':'Input_FALast'}, axis=1)
print(len(Matched))
Matched.head(4)

17
Warning: Total number of columns (35) exceeds max_columns (20). Falling back to pandas display.

[12]:

	RA_Manuscript ID	RA_Date of Rejection	RA_Reject Reason	RA_Title	RA_First Author	RA_Corr Author	RA_Co-Authors	RA_Subject Category	RA_Editor	RA_Submitted Journal	RA_Article Type	RA_Keywords	RA_Custom	RA_Funders	RA_Keywords_Or	Input_Keywords_And	Input_FALast	Input_CALast	Dim_id	Dim_title	Dim_altmetric	Dim_authors_count	Dim_date_print	Dim_field_citation_ratio	Dim_publisher	Dim_recent_citations	Dim_relative_citation_ratio	Dim_score	Dim_times_cited	Dim_journal.id	Dim_journal.title	Dim_Reject_ManID	Dim_FirstAuthor	Dim_LastAuthor	Dim_CorrAuthor
0	JSS76145	2001-04-01	Reject Open	Erythrodiol 3 acetate pentacyclic triterpenoi...	Moon, Hyung-In	Chung, Jin Ho	Moon, Hyung-In; Seo, Dong Wan; Kim, Kyu-Han; C...	NaN	Kim, Soo-jin	Science Serial	NaN	Humans, Enzyme Inhibitors/isolation & purifica...	NaN	NaN	Humans OR Enzyme Inhibitors isolation purifi...	Humans AND Enzyme Inhibitors isolation purif...	Moon	Chung	pub.1035176145	RETRACTED: Erythrodiol-3-acetate, pentacyclic ...	3.0	6.0	2005-03	0.57	Elsevier	0.0	0.10	314.917360	6.0	jour.1089348	Journal of Ethnopharmacology	JSS76145	Moon	Chung	Moon,Chung
1	JSS50060	2012-06-23	Reject Open	A Programmable Dual RNA Guided DNA Endonucleas...	Jinek, Martin	Fonfara, I	Jinek, Martin; Chylinski, Krzysztof; Fonfara, ...	NaN	Garcia, Luis	Science Serial	NaN	Deoxyribonucleases, Type II Site-Specific/meta...	NaN	NaN	Deoxyribonucleases OR Type II Site Specific me...	Deoxyribonucleases AND Type II Site Specific m...	Jinek	Fonfara	pub.1041850060	A Programmable Dual-RNA–Guided DNA Endonucleas...	4390.0	6.0	2012-08-17	1097.75	American Association for the Advancement of Sc...	3442.0	272.63	121.100395	14223.0	jour.1346339	Science	JSS50060	Jinek	Charpentier
2	JSS48881	1998-01-01	EDREJECT	Ileal lymphoid nodular hyperplasia non specif...	Wakefield, AJ	Wakefield, AJ	Wakefield, AJ; Murch, SH; Anthony, A; Linnell,...	NaN	Patel, Priya	Chemistry Compendium	NaN	Developmental Disabilities/etiology*, Child, H...	NaN	NaN	Developmental Disabilities etiology OR Child ...	Developmental Disabilities etiology AND Child...	Wakefield	Wakefield	pub.1047248881	RETRACTED: Ileal-lymphoid-nodular hyperplasia,...	4690.0	13.0	1998-02	NaN	Elsevier	196.0	36.24	171.698400	2328.0	jour.1077219	The Lancet	JSS48881	Wakefield	Walker-Smith	Wakefield
3	JSS76940	2005-07-17	Reject Open	Suppression of RNA Recognition by Toll like Re...	Kariko, Katalin	Weissman, Drew	Karikó, Katalin; Buckstein, Michael; Ni, Houpi...	NaN	Garcia, Luis	Science Serial	NaN	Dendritic Cells/metabolism, Signal Transductio...	NaN	NaN	Dendritic Cells metabolism OR Signal Transduct...	Dendritic Cells metabolism AND Signal Transduc...	Kariko	Weissman	pub.1047376940	Suppression of RNA Recognition by Toll-like Re...	3388.0	4.0	2005-08	164.50	Elsevier	724.0	25.73	193.518800	1957.0	jour.1112054	Immunity	JSS76940	Karikó	Weissman	Karikó

6. Retrieve Journal attributes and add to Dataframe#

[13]:

##Make a second call to get Journal Attributes and join to main table:

JournalList = Matched['Dim_journal.id'].dropna().tolist()
JournalList = list(dict.fromkeys(JournalList))
print(JournalList)

ChunkNumber = 1
ChunkSize = 50  #<--  If you get an error, reduce this number.  Max is 500; 200 is a great starting point.
TotalChunks = round(0.5+(len(JournalList)/ChunkSize))
# Find publications that cited the list above
q = """search source_titles where id in {}
              return source_titles[id+title+snip+sjr+issn+start_year+journal_lists]"""
results = []
for chunk in (list(chunks_of(list(JournalList), ChunkSize))):
    print("Working on Chunk #",(ChunkNumber)," of ",TotalChunks)
    ChunkNumber = ChunkNumber+1
    data = dsl.query_iterative(q.format(json.dumps(chunk)), verbose=False)
    results += data.source_titles
    time.sleep(1)
Journals = pd.DataFrame().from_dict(results)
print("Publications found: ", len(Journals))
Journals.drop_duplicates(subset='id', inplace=True)
print("Unique publications found: ", len(Journals))
Journals = Journals.add_prefix("Jour_")
Journals.head(5)

Matched = pd.merge(
    left=Matched,
    right=Journals,
    left_on=['Dim_journal.id'],
    right_on=['Jour_id'],
    how='left'
)

Matched.head(9)

['jour.1089348', 'jour.1346339', 'jour.1077219', 'jour.1112054', 'jour.1018957', 'jour.1134140', 'jour.1049812', 'jour.1299119', 'jour.1105222', 'jour.1087229', 'jour.1032854', 'jour.1115214', 'jour.1113716', 'jour.1029779']
Working on Chunk # 1  of  1
Publications found:  14
Unique publications found:  14
Warning: Total number of columns (42) exceeds max_columns (20). Falling back to pandas display.

[13]:

	RA_Manuscript ID	RA_Date of Rejection	RA_Reject Reason	RA_Title	RA_First Author	RA_Corr Author	RA_Co-Authors	RA_Subject Category	RA_Editor	RA_Submitted Journal	RA_Article Type	RA_Keywords	RA_Custom	RA_Funders	RA_Keywords_Or	Input_Keywords_And	Input_FALast	Input_CALast	Dim_id	Dim_title	Dim_altmetric	Dim_authors_count	Dim_date_print	Dim_field_citation_ratio	Dim_publisher	Dim_recent_citations	Dim_relative_citation_ratio	Dim_score	Dim_times_cited	Dim_journal.id	Dim_journal.title	Dim_Reject_ManID	Dim_FirstAuthor	Dim_LastAuthor	Dim_CorrAuthor	Jour_id	Jour_issn	Jour_journal_lists	Jour_sjr	Jour_snip	Jour_start_year	Jour_title
0	JSS76145	2001-04-01	Reject Open	Erythrodiol 3 acetate pentacyclic triterpenoi...	Moon, Hyung-In	Chung, Jin Ho	Moon, Hyung-In; Seo, Dong Wan; Kim, Kyu-Han; C...	NaN	Kim, Soo-jin	Science Serial	NaN	Humans, Enzyme Inhibitors/isolation & purifica...	NaN	NaN	Humans OR Enzyme Inhibitors isolation purifi...	Humans AND Enzyme Inhibitors isolation purif...	Moon	Chung	pub.1035176145	RETRACTED: Erythrodiol-3-acetate, pentacyclic ...	3.0	6.0	2005-03	0.57	Elsevier	0.0	0.10	314.917360	6.0	jour.1089348	Journal of Ethnopharmacology	JSS76145	Moon	Chung	Moon,Chung	jour.1089348	[0378-8741, 1872-7573]	[Norwegian register level 1, ERA 2018, UGC Jou...	0.936	1.55	1978.0	Journal of Ethnopharmacology
1	JSS50060	2012-06-23	Reject Open	A Programmable Dual RNA Guided DNA Endonucleas...	Jinek, Martin	Fonfara, I	Jinek, Martin; Chylinski, Krzysztof; Fonfara, ...	NaN	Garcia, Luis	Science Serial	NaN	Deoxyribonucleases, Type II Site-Specific/meta...	NaN	NaN	Deoxyribonucleases OR Type II Site Specific me...	Deoxyribonucleases AND Type II Site Specific m...	Jinek	Fonfara	pub.1041850060	A Programmable Dual-RNA–Guided DNA Endonucleas...	4390.0	6.0	2012-08-17	1097.75	American Association for the Advancement of Sc...	3442.0	272.63	121.100395	14223.0	jour.1346339	Science	JSS50060	Jinek	Charpentier		jour.1346339	[0036-8075, 1095-9203]	[Nature Index journals, ERA 2018, UGC Journal ...	11.900	9.28	1880.0	Science
2	JSS48881	1998-01-01	EDREJECT	Ileal lymphoid nodular hyperplasia non specif...	Wakefield, AJ	Wakefield, AJ	Wakefield, AJ; Murch, SH; Anthony, A; Linnell,...	NaN	Patel, Priya	Chemistry Compendium	NaN	Developmental Disabilities/etiology*, Child, H...	NaN	NaN	Developmental Disabilities etiology OR Child ...	Developmental Disabilities etiology AND Child...	Wakefield	Wakefield	pub.1047248881	RETRACTED: Ileal-lymphoid-nodular hyperplasia,...	4690.0	13.0	1998-02	NaN	Elsevier	196.0	36.24	171.698400	2328.0	jour.1077219	The Lancet	JSS48881	Wakefield	Walker-Smith	Wakefield	jour.1077219	[0140-6736, 1474-547X]	[ERA 2018, UGC Journal List Group II, VABB-SHW...	12.100	33.70	1823.0	The Lancet
3	JSS76940	2005-07-17	Reject Open	Suppression of RNA Recognition by Toll like Re...	Kariko, Katalin	Weissman, Drew	Karikó, Katalin; Buckstein, Michael; Ni, Houpi...	NaN	Garcia, Luis	Science Serial	NaN	Dendritic Cells/metabolism, Signal Transductio...	NaN	NaN	Dendritic Cells metabolism OR Signal Transduct...	Dendritic Cells metabolism AND Signal Transduc...	Kariko	Weissman	pub.1047376940	Suppression of RNA Recognition by Toll-like Re...	3388.0	4.0	2005-08	164.50	Elsevier	724.0	25.73	193.518800	1957.0	jour.1112054	Immunity	JSS76940	Karikó	Weissman	Karikó	jour.1112054	[1074-7613, 1097-4180]	[Nature Index journals, ERA 2018, UGC Journal ...	13.600	6.84	1984.0	Immunity
4	JSS61136	2009-10-07	EDREJECT	Tracheobronchial transplantation with a stem c...	Macchiarini, Paolo	Jungebluth, P.	Jungebluth, Philipp; Alici, Evren; Baiguera, S...	NaN	Kim, Soo-jin	Chemistry Compendium	NaN	Epoetin Alfa, Male, Recombinant Proteins/thera...	NaN	NaN	Epoetin Alfa OR Male OR Recombinant Proteins t...	Epoetin Alfa AND Male AND Recombinant Proteins...	Macchiarini	Jungebluth	pub.1049161136	RETRACTED: Tracheobronchial transplantation wi...	243.0	24.0	2011-12	104.28	Elsevier	10.0	9.83	222.500670	395.0	jour.1077219	The Lancet	JSS61136	Jungebluth	Macchiarini	Macchiarini	jour.1077219	[0140-6736, 1474-547X]	[ERA 2018, UGC Journal List Group II, VABB-SHW...	12.100	33.70	1823.0	The Lancet
5	JSS62519	1990-06-10	Reject	Superconductivity in molecular crystals induce...	Schön, J. H.	Batlogg, B.	Schön, J. H.; Kloc, Ch.; Batlogg, B.	NaN	Patel, Priya	Medical Monthly	NaN	molecular crystals, charge injection, charge-t...	NaN	NaN	molecular crystals OR charge injection OR char...	molecular crystals AND charge injection AND ch...	Schön	Batlogg	pub.1050062519	RETRACTED ARTICLE: Superconductivity in molecu...	9.0	3.0	2000-08-17	29.45	Springer Nature	2.0	0.91	14.369866	151.0	jour.1018957	Nature	JSS62519	Schön	Batlogg	Batlogg	jour.1018957	[0028-0836, 1476-4687]	[Nature Index journals, ERA 2018, UGC Journal ...	18.500	11.60	1869.0	Nature
6	JSS15074	2005-02-06	Reject Open	New Stellar Orbits around the Galactic Center ...	Ghez, A. M.	Ghez, A. M.	Ghez, A. M.; Salim, S.; Hornstein, S. D.; Tann...	NaN	Smith, John	Medical Monthly	NaN	dark mass, black hole, young stars, m telescope	NaN	NaN	dark mass OR black hole OR young stars OR m te...	dark mass AND black hole AND young stars AND m...	Ghez	Ghez	pub.1046439810	Stellar Dynamics at the Galactic Center with a...	3.0	3.0	2005-04	18.51	American Astronomical Society	6.0	NaN	40.507088	110.0	jour.1134140	The Astrophysical Journal	JSS15074	Weinberg	Ghez		jour.1134140	[0004-637X, 1538-4357]	[DOAJ, ERA 2018, UGC Journal List Group II, No...	1.910	1.15	1895.0	The Astrophysical Journal
7	JSS42224	2017-05-09	Reject and Refer without Review	The Forever Diamond Contrast Reversals Along ...	Flynn, Oliver J.	Shapiro, Arthur	Flynn, Oliver J.; Shapiro, Arthur Gene	NaN	Garcia, Luis	Science Serial	NaN	luminous phase, modulation, temporal contrast,...	NaN	NaN	luminous phase OR modulation OR temporal contr...	luminous phase AND modulation AND temporal con...	Flynn	Shapiro	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8	JSS35047	2019-08-07	Reject and Refer without Review	Potential Applications to Treat Cancer with Gr...	Zhang, Dan	Gu, Yan	Zhang, Dan; Ma, Xin-lei; Gu, Yan; Huang, He; Z...	NaN	Patel, Priya	Chemistry Compendium	NaN	green synthesis, nanoparticles, biological ent...	NaN	NaN	green synthesis OR nanoparticles OR biological...	green synthesis AND nanoparticles AND biologic...	Zhang	Gu	pub.1132135047	RETRACTED: Green Synthesis of Metallic Nanopar...	1.0	5.0	NaN	NaN	Frontiers	228.0	12.40	35.232506	396.0	jour.1049812	Frontiers in Chemistry	JSS35047	Zhang	Zhang	Zhang	jour.1049812	[2296-2646]	[Norwegian register level 1, DOAJ, UGC Journal...	0.818	1.05	2012.0	Frontiers in Chemistry

7. Add Matching Score#

At this point we have a dataframe with our rejected articles paired with the metadata for the Dimensions publication that most closely resembles each.

However, the best match isn’t necessarily an actual match, so you must add a review process before analyzing or drawing any conclusions from this dataframe. In this section, we will quantify the quality of the match to aid in this review process. Levenshtein’s ratio measures the similarity between two strings (in this case the search title and the found title) by calculating the minimum number of edits (insertions, deletions, or substitutions) needed to transform one string into the other. The lev.ratio function normalizes this distance and returns a score from 0 to 100, with higher scores indicating closer matches. This score appears in the dataframe as TitleRatio.

By scanning the results and considering the volume of data you’re working with, your level of patience and your tolerance for false positives/negatives, you can make a business decision to accept any matches above a particular score or to use the score to streamline any human validation process.

[14]:

import Levenshtein as lev

Matched['TitleRatio'] = Matched.dropna(subset=['RA_Title', 'Dim_title']).apply(
    lambda x: lev.ratio(x.RA_Title, x.Dim_title) * 100, axis=1)

Matched['FirstAuthorRatio'] = Matched.dropna(subset=['RA_First Author', 'Dim_FirstAuthor']).apply(
    lambda x: lev.ratio(x['Input_FALast'], x['Dim_FirstAuthor']) * 100, axis=1)

Matched['CorrAuthorRatio'] = Matched.dropna(subset=['RA_Corr Author', 'Dim_CorrAuthor']).apply(
    lambda x: lev.ratio(x['Input_CALast'], x['Dim_CorrAuthor']) * 100, axis=1)

print(len(Matched))
Matched.head(3)

[14]:

	RA_Manuscript ID	RA_Date of Rejection	RA_Reject Reason	RA_Title	RA_First Author	RA_Corr Author	RA_Co-Authors	RA_Subject Category	RA_Editor	RA_Submitted Journal	RA_Article Type	RA_Keywords	RA_Custom	RA_Funders	RA_Keywords_Or	Input_Keywords_And	Input_FALast	Input_CALast	Dim_id	Dim_title	Dim_altmetric	Dim_authors_count	Dim_date_print	Dim_field_citation_ratio	Dim_publisher	Dim_recent_citations	Dim_relative_citation_ratio	Dim_score	Dim_times_cited	Dim_journal.id	Dim_journal.title	Dim_Reject_ManID	Dim_FirstAuthor	Dim_LastAuthor	Dim_CorrAuthor	Jour_id	Jour_issn	Jour_journal_lists	Jour_sjr	Jour_snip	Jour_start_year	Jour_title	TitleRatio	FirstAuthorRatio	CorrAuthorRatio
0	JSS76145	2001-04-01	Reject Open	Erythrodiol 3 acetate pentacyclic triterpenoi...	Moon, Hyung-In	Chung, Jin Ho	Moon, Hyung-In; Seo, Dong Wan; Kim, Kyu-Han; C...	NaN	Kim, Soo-jin	Science Serial	NaN	Humans, Enzyme Inhibitors/isolation & purifica...	NaN	NaN	Humans OR Enzyme Inhibitors isolation purifi...	Humans AND Enzyme Inhibitors isolation purif...	Moon	Chung	pub.1035176145	RETRACTED: Erythrodiol-3-acetate, pentacyclic ...	3.0	6.0	2005-03	0.57	Elsevier	0.0	0.10	314.917360	6.0	jour.1089348	Journal of Ethnopharmacology	JSS76145	Moon	Chung	Moon,Chung	jour.1089348	[0378-8741, 1872-7573]	[Norwegian register level 1, ERA 2018, UGC Jou...	0.936	1.55	1978.0	Journal of Ethnopharmacology	90.604027	100.0	66.666667
1	JSS50060	2012-06-23	Reject Open	A Programmable Dual RNA Guided DNA Endonucleas...	Jinek, Martin	Fonfara, I	Jinek, Martin; Chylinski, Krzysztof; Fonfara, ...	NaN	Garcia, Luis	Science Serial	NaN	Deoxyribonucleases, Type II Site-Specific/meta...	NaN	NaN	Deoxyribonucleases OR Type II Site Specific me...	Deoxyribonucleases AND Type II Site Specific m...	Jinek	Fonfara	pub.1041850060	A Programmable Dual-RNA–Guided DNA Endonucleas...	4390.0	6.0	2012-08-17	1097.75	American Association for the Advancement of Sc...	3442.0	272.63	121.100395	14223.0	jour.1346339	Science	JSS50060	Jinek	Charpentier		jour.1346339	[0036-8075, 1095-9203]	[Nature Index journals, ERA 2018, UGC Journal ...	11.900	9.28	1880.0	Science	94.805195	100.0	0.000000
2	JSS48881	1998-01-01	EDREJECT	Ileal lymphoid nodular hyperplasia non specif...	Wakefield, AJ	Wakefield, AJ	Wakefield, AJ; Murch, SH; Anthony, A; Linnell,...	NaN	Patel, Priya	Chemistry Compendium	NaN	Developmental Disabilities/etiology*, Child, H...	NaN	NaN	Developmental Disabilities etiology OR Child ...	Developmental Disabilities etiology AND Child...	Wakefield	Wakefield	pub.1047248881	RETRACTED: Ileal-lymphoid-nodular hyperplasia,...	4690.0	13.0	1998-02	NaN	Elsevier	196.0	36.24	171.698400	2328.0	jour.1077219	The Lancet	JSS48881	Wakefield	Walker-Smith	Wakefield	jour.1077219	[0140-6736, 1474-547X]	[ERA 2018, UGC Journal List Group II, VABB-SHW...	12.100	33.70	1823.0	The Lancet	87.782805	100.0	100.000000

8. Export for Analysis or dashboard feed:#

[15]:

DimensionsRAExport = Matched
# Export the DataFrame to an Excel file
file_name = "DimensionsRAExport.xlsx"
DimensionsRAExport.to_excel(file_name, index=False)
if 'google.colab' in sys.modules:
    files.download(file_name)

[16]:

#Alternative .csv export
DimensionsRAExport = Matched
file_name = "DimensionsRAExport.csv"
DimensionsRAExport.to_csv(file_name, index=False)
if 'google.colab' in sys.modules:
    files.download(file_name)

9. Conclusion#

In this tutorial we have used the fuzzy, full-text capability of the Dimensions API to identify the final outcome of rejected articles. Our next steps would be to evaluate the bibliometrics of these publications and use the results of that analysis to inform future accept/reject decisions.

Note

The Dimensions Analytics API allows to carry out sophisticated research data analytics tasks like the ones described on this website. Check out also the associated Github repository for examples, the source code of these tutorials and much more.