Comprehensive database of academic journal impact factors, JCR quartiles, and CAS block classifications for 2025.

Journal of Chemistry Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Chemistry is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles on all aspects of fundamental and applied chemistry. Journal of Chemistry is archived in Portico, which provides permanent archiving for electronic scholarly journals, as well as via the LOCKSS initiative. It operates a fully open access publishing model which allows open global access to its published content. This model is supported through Article Processing Charges. Journal of Chemistry is included in many leading abstracting and indexing databases. For a complete list, click here. The most recent Impact Factor for Journal of Chemistry is 1.727 according to the 2018 Journal Citation Reports released by Clarivate Analytics in 2019. The journal’s most recent CiteScore is 1.32 according to the CiteScore 2018 metrics released by Scopus. Abstracting and Indexing Academic Search Alumni Edition Academic Search Complete AgBiotech Net AgBiotech News and Information AGRICOLA Agricultural Economics Database Agricultural Engineering Abstracts Agroforestry Abstracts Animal Breeding Abstracts Animal Science Database Biofuels Abstracts Botanical Pesticides CAB Abstracts Chemical Abstracts Service (CAS) CNKI Scholar Crop Physiology Abstracts Crop Science Database Directory of Open Access Journals (DOAJ) EBSCOhost Connection EBSCOhost Research Databases Elsevier BIOBASE - Current Awareness in Biological Sciences (CABS) EMBIOlogy Energy and Power Source Global Health Google Scholar J-Gate Portal Journal Citation Reports - Science Edition Open Access Journals Integrated Service System Project (GoOA) Primo Central Index Reaxys Science Citation Index Expanded Scopus Textile Technology Index The Summon Service WorldCat Discovery Services

Journal of Big Data Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material. All articles published by the Journal of Big Data are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. As authors of articles published in the Journal of Big Data you are the copyright holders of your article and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate your article, according to the SpringerOpen copyright and license agreement. For those of you who are US government employees or are prevented from being copyright holders for similar reasons, SpringerOpen can accommodate non-standard copyright lines.

Academic journals indicators developed from the information contained in the Scopus database (Elsevier B.V.). These indicators can be used to assess and analyze scientific domains.

Data sharing is crucial to the advancement of science because it facilitates collaboration, transparency, reproducibility, criticism, and re-analysis. Publishers are well-positioned to promote sharing of research data by implementing data sharing policies. While there is an increasing trend toward requiring data sharing, not all journals mandate that data be shared at the time of publication. In this study, we extended previous work to analyze the data sharing policies of 447 journals across several scientific disciplines, including biology, clinical sciences, mathematics, physics, and social sciences. Our results showed that only a small percentage of journals require data sharing as a condition of publication, and that this varies across disciplines and Impact Factors. Both Impact Factors and discipline are associated with the presence of a data sharing policy. Our results suggest that journals with higher Impact Factors are more likely to have data sharing policies; use shared data in peer review; require deposit of specific data types into publicly available data banks; and refer to reproducibility as a rationale for sharing data. Biological science journals are more likely than social science and mathematics journals to require data sharing.

This is the open data for the preprint "Measuring Back: Bibliodiversity and the Journal Impact Factor brand. A Case study of IF-journals included in the 2021 Journal Citations Report."

International Journal of Data Science and Analytics Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Data Science and Analytics - Data Science has been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. The field encompasses the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. It also tackles related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation. The International Journal of Data Science and Analytics (JDSA) brings together thought leaders, researchers, industry practitioners, and potential users of data science and analytics, to develop the field, discuss new trends and opportunities, exchange ideas and practices, and promote transdisciplinary and cross-domain collaborations.

The Biodiversity Footprint Database contains global consumption-based, monetary, biodiversity impact factors for 44 countries and five rest of the world regions. The dataset has been compiled by combining information from EXIOBASE and LC-IMPACT databases. In addition, the EXIOBASE database has been analyzed with the pymrio analysis tool to determine the geographical location of the consumption-based biodiversity impacts. The mid-point impact factors from EXIOBASE are based on 2019 data, but the regional analysis with pymrio is based on 2011 data. EXIOBASE version 3.8.2 was used and LC-IMPACT version 1.3. The data is currently non peer-reviewed and under submission. The database will be open access after publication. The preprint of the manuscript can be found from: https://doi.org/10.48550/arXiv.2309.14186

About the units

The unit used in the database is the biodiversity equivalent (BDe). The biodversity equivalent, as we call it, is more commonly known as the global potentially disappeared fraction of species (global PDF, Verones et al., 2020). Thus, the monetary biodiversity impact factors are presented in the form BDe/€.

Prices are in basic prices and the conversion factors to transform purchaser prices (e.g. financial accounting prices) to basic prices are provided for Finland (and later for all regions), based on EXIOBASE supply and use tables (SUT).

Content of files

BiodiversityFootprintDatabase.xlsx

The biodiversity impact factors, regional abbreviations and basic price conversion factors for Finland.

BiodiversityFootprintDatabase_DetailedData.zip

The detailed data used to combine EXIOBASE and LC-IMPACT data after the EXIOBASE data was analyzed with the pymrio tool. Contains folders for each driver of biodiversity loss according to the LC-IMPACT classification.

20220406_Exio3stressorcode _2011.py & 20220406_Exio3StressorAggregationCode_2011.py

The pymrio codes that were used to analyze EXIOBASE and the geographical location of the drivers of biodiversity loss (mid-point indicators).

Background: The assessment of scientific publications is an integral part of the scientific process. Here we investigate three methods of assessing the merit of a scientific paper: subjective post-publication peer review, the number of citations gained by a paper and the impact factor of the journal in which the article was published. Methodology/principle findings: We investigate these methods using two datasets in which subjective post-publication assessments of scientific publications have been made by experts. We find that there are moderate, but statistically significant, correlations between assessor scores, when two assessors have rated the same paper, and between assessor score and the number of citations a paper accrues. However, we show that assessor score depends strongly on the journal in which the paper is published, and that assessors tend to over-rate papers published in journals with high impact factors. If we control for this bias, we find that the correlation between assessor scores and between assessor score and the number of citations is weak, suggesting that scientists have little ability to judge either the intrinsic merit of a paper or its likely impact. We also show that the number of citations a paper receives is an extremely error-prone measure of scientific merit. Finally, we argue that the impact factor is likely to be a poor measure of merit, since it depends on subjective assessment. Conclusions: We conclude that the three measures of scientific merit considered here are poor; in particular subjective assessments are an error-prone, biased and expensive method by which to assess merit. We argue that the impact factor may be the most satisfactory of the methods we have considered, since it is a form of pre-publication review. However, we emphasise that it is likely to be a very error-prone measure of merit that is qualitative, not quantitative.

Datasets for publication: 'Measuring the excellence contribution at the journal level: An alternative to Garfield's Impact Factor'.

Overview. Overview of the number of journals, publications, excellent publications and multidisciplinarity for each category considered.

ALL. Journal indicators for all the document types by JCR category.

ALL_JCR. Journal indicators for all the document types by JCR category (only journals indexed in the JCR category are taken into account).

AR. Journal indicators for only articles and reviews by JCR category.

AR_JCR. Journal indicators for only articles and reviews by JCR category (only journals indexed in the JCR category are taken into account).

Here are the data for papers [1,2]. The 1st excel sheet ("theory") has data for Figures 1, 2 of [1]. The 2nd sheet ("JCR data") has data for Figures 3, 4, 5, 6 of [1], and Figure 1 of [2].A. Data in the "theory" sheet:2nd row: Citation count, c, of a single paper published by a journal of Impact Factor f1=10 and biennial size N1. We have chosen c to range from 0 to 1000 in our data. 2nd column: biennial size N1 of journal. We have chosen N1 to range from 10 to 2500 in our data. The data in the cells from C3 to EC283 in the sheet are calculations of the volatility, Δf(c), as defined in Eq. (4) of [1].B. Data in the "JCR data" sheet:The publication and citation data below are from each journal's individual Journal Citation Report for 2017. Impact Factor. These are data from the 2017 Journal Citation Reports (JCR).Journal biennial size, N2Y. This is the number of articles & reviews published in 2015-2016 by each journal.Citation average, f. This is the average number of citations received in 2017 by the articles & reviews published in 2015-2016.Volatility, Δf(c*): This is defined as f - f* (see below for f*)Relative volatility, Δfr(c*): This is defined as (f - f*)/f* (see below for f*)Top-cited paper, c*: This is the citation count of the top-cited paper in each journal, in the year 2017. Citation average excluding top-cited paper, f*: This is the average number of citations received in 2017 by the articles & reviews published in 2015-2016, once we exclude the top-cited paper (article or review). AcknowledgmentThis work uses data, accessed through Columbia University, from the Web of Science and Journal Citation Reports (2017) with explicit consent from Clarivate Analytics.References [1] M. Antonoyiannakis, Impact Factor volatility to a single paper: A comprehensive analysis, Quantitative Science Studies (2020, accepted), https://arxiv.org/abs/1911.02533[2] M. Antonoyiannakis, How a single paper affects the Impact Factor: Implications for Scholarly Publishing, Proceedings of the 17th Conference of the International Society on Scientometrics & Informetrics, vol. II, 2306-2313 (2019), https://arxiv.org/abs/1906.02660

The journals’ author guidelines and/or editorial policies were examined on whether they take a stance with regard to the availability of the underlying data of the submitted article. The mere explicated possibility of providing supplementary material along with the submitted article was not considered as a research data policy in the present study. Furthermore, the present article excluded source codes or algorithms from the scope of the paper and thus policies related to them are not included in the analysis of the present article.

For selection of journals within the field of neurosciences, Clarivate Analytics’ InCites Journal Citation Reports database was searched using categories of neurosciences and neuroimaging. From the results, journals with the 40 highest Impact Factor (for the year 2017) indicators were extracted for scrutiny of research data policies. Respectively, the selection journals within the field of physics was created by performing a similar search with the categories of physics, applied; physics, atomic, molecular & chemical; physics, condensed matter; physics, fluids & plasmas; physics, mathematical; physics, multidisciplinary; physics, nuclear and physics, particles & fields. From the results, journals with the 40 highest Impact Factor indicators were again extracted for scrutiny. Similarly, the 40 journals representing the field of operations research were extracted by using the search category of operations research and management.

Journal-specific data policies were sought from journal specific websites providing journal specific author guidelines or editorial policies. Within the present study, the examination of journal data policies was done in May 2019. The primary data source was journal-specific author guidelines. If journal guidelines explicitly linked to the publisher’s general policy with regard to research data, these were used in the analyses of the present article. If journal-specific research data policy, or lack of, was inconsistent with the publisher’s general policies, the journal-specific policies and guidelines were prioritized and used in the present article’s data. If journals’ author guidelines were not openly available online due to, e.g., accepting submissions on an invite-only basis, the journal was not included in the data of the present article. Also journals that exclusively publish review articles were excluded and replaced with the journal having the next highest Impact Factor indicator so that each set representing the three field of sciences consisted of 40 journals. The final data thus consisted of 120 journals in total.

‘Public deposition’ refers to a scenario where researcher deposits data to a public repository and thus gives the administrative role of the data to the receiving repository. ‘Scientific sharing’ refers to a scenario where researcher administers his or her data locally and by request provides it to interested reader. Note that none of the journals examined in the present article required that all data types underlying a submitted work should be deposited into a public data repositories. However, some journals required public deposition of data of specific types. Within the journal research data policies examined in the present article, these data types are well presented by the Springer Nature policy on “Availability of data, materials, code and protocols” (Springer Nature, 2018), that is, DNA and RNA data; protein sequences and DNA and RNA sequencing data; genetic polymorphisms data; linked phenotype and genotype data; gene expression microarray data; proteomics data; macromolecular structures and crystallographic data for small molecules. Furthermore, the registration of clinical trials in a public repository was also considered as a data type in this study. The term specific data types used in the custom coding framework of the present study thus refers to both life sciences data and public registration of clinical trials. These data types have community-endorsed public repositories where deposition was most often mandated within the journals’ research data policies.

The term ‘location’ refers to whether the journal’s data policy provides suggestions or requirements for the repositories or services used to share the underlying data of the submitted works. A mere general reference to ‘public repositories’ was not considered a location suggestion, but only references to individual repositories and services. The category of ‘immediate release of data’ examines whether the journals’ research data policy addresses the timing of publication of the underlying data of submitted works. Note that even though the journals may only encourage public deposition of the data, the editorial processes could be set up so that it leads to either publication of the research data or the research data metadata in conjunction to publishing of the submitted work.

Polymer engineering and science Impact Factor 2024-2025 - ResearchHelpDesk - Polymer engineering and science - Every day, the Society of Plastics Engineers (SPE) takes action to help companies in the plastics industry succeed. How? By spreading knowledge, strengthening skills and promoting plastics. Employing these vital strategies, Polymer engineering and science - SPE has helped the plastics industry thrive for over 60 years. In the process, we've developed a 25,000-member network of leading engineers and other plastics professionals, including technicians, salespeople, marketers, retailers, and representatives from tertiary industries. For more than 30 years, Polymer Engineering & Science has been one of the most highly regarded journals in the field, serving as a forum for authors of treatises on the cutting edge of polymer science and technology. The importance of PE&S is underscored by the frequent rate at which its articles are cited, especially by other publications - literally thousands of times a year. Engineers, researchers, technicians, and academicians worldwide are looking to PE&S for the valuable information they need. There are special issues compiled by distinguished guest editors. These contain proceedings of symposia on such diverse topics as polyblends, mechanics of plastics and polymer welding. Abstracting and Indexing Information Academic ASAP (GALE Cengage) Advanced Technologies & Aerospace Database (ProQuest) Applied Science & Technology Index/Abstracts (EBSCO Publishing) CAS: Chemical Abstracts Service (ACS) CCR Database (Clarivate Analytics) Chemical Abstracts Service/SciFinder (ACS) Chemistry Server Reaction Center (Clarivate Analytics) ChemWeb (ChemIndustry.com) Chimica Database (Elsevier) COMPENDEX (Elsevier) Current Contents: Engineering, Computing & Technology (Clarivate Analytics) Current Contents: Physical, Chemical & Earth Sciences (Clarivate Analytics) Expanded Academic ASAP (GALE Cengage) InfoTrac (GALE Cengage) Journal Citation Reports/Science Edition (Clarivate Analytics) Materials Science & Engineering Database (ProQuest) PASCAL Database (INIST/CNRS) Polymer Library (iSmithers RAPRA) ProQuest Central (ProQuest) ProQuest Central K-462 Reaction Citation Index (Clarivate Analytics) Research Library (ProQuest) Research Library Prep (ProQuest) Science Citation Index (Clarivate Analytics) Science Citation Index Expanded (Clarivate Analytics) SciTech Premium Collection (ProQuest) SCOPUS (Elsevier) STEM Database (ProQuest) Technology Collection (ProQuest) Web of Science (Clarivate Analytics)

Objective: To determine the top 100-ranked (by impact factor) clinical journals' policies toward publishing research previously published on preprint servers (preprints).

Design: Cross sectional. Main outcome measures: Editorial guidelines toward preprints, journal rank by impact factor.

Results: 86 (86%) of the journals examined will consider papers previously published as preprints (preprints), 13 (13%) determine their decision on a case-by-case basis, and 1 (1%) does not allow preprints.

Conclusions: We found wide acceptance of publishing preprints in the clinical research community, although researchers may still face uncertainty that their preprints will be accepted by all of their target journals.

Methods We examined journal policies of the 100 top-ranked clinical journals using the 2018 impact factors as reported by InCites Journal Citation Reports (JCR). First, we examined all journals with an impact factor greater than 5, and then we manually screened by title and category do identify the first 100 clinical journals. We included only those that publish original research. Next, we checked each journal's editorial policy on preprints. We examined, in order, the journal website, the publisher website, the Transpose Database, and the first 10 pages of a Google search with the journal name and the term "preprint." We classified each journal's policy, as shown in this dataset, as allowing preprints, determining based on preprint status on a case-by-case basis, and not allowing any preprints. We collected data on April 23, 2020.

(Full methods can also be found in previously published paper.)

Journals & Ranking

An academic journal or research journal is a periodical publication in which research articles relating to a particular academic discipline is published, according to Wikipedia. Currently, there are more than 25,000 peer-reviewed journals that are indexed in citation index databases such as Scopus and Web of Science. These indexes are ranked on the basis of various metrics such as CiteScore, H-index, etc. The metrics are calculated from yearly citation data of the journal. A lot of efforts are given to make a metric that reflects the journal's quality.

Journal Ranking Dataset

This is a comprehensive dataset on the academic journals coving their metadata information as well as citation, metrics, and ranking information. Detailed data on their subject area is also given in this dataset. The dataset is collected from the following indexing databases: - Scimago Journal Ranking - Scopus - Web of Science Master Journal List

The data is collected by scraping and then it was cleaned, details of which can be found in HERE.

Key Features

• Rank: Overall rank of journal (derived from sorted SJR index).
• Title: Name or title of journal.
• OA: Open Access or not.
• Country: Country of origin.
• SJR-index: A citation index calculated by Scimago.
• CiteScore: A citation index calculated by Scopus.
• H-index: Hirsh index, the largest number h such that at least h articles in that journal were cited at least h times each.
• Best Quartile: Top Q-index or quartile a journal has in any subject area.
• Best Categories: Subject areas with top quartile.
• Best Subject Area: Highest ranking subject area.
• Best Subject Rank: Rank of the highest ranking subject area.
• Total Docs.: Total number of documents of the journal.
• Total Docs. 3y: Total number of documents in the past 3 years.
• Total Refs.: Total number of references of the journal.
• Total Cites 3y: Total number of citations in the past 3 years.
• Citable Docs. 3y: Total number of citable documents in the past 3 years.
• Cites/Doc. 2y: Total number of citations divided by the total number of documents in the past 2 years.
• Refs./Doc.: Total number of references divided by the total number of documents.
• Publisher: Name of the publisher company of the journal.
• Core Collection: Web of Science core collection name.
• Coverage: Starting year of coverage.
• Active: Active or inactive.
• In-Press: Articles in press or not.
• ISO Language Code: Three-letter ISO 639 code for language.
• ASJC Codes: All Science Journal Classification codes for the journal.

Rest of the features provide further details on the journal's subject area or category: - Life Sciences: Top level subject area. - Social Sciences: Top level subject area. - Physical Sciences: Top level subject area. - Health Sciences: Top level subject area. - 1000 General: ASJC main category. - 1100 Agricultural and Biological Sciences: ASJC main category. - 1200 Arts and Humanities: ASJC main category. - 1300 Biochemistry, Genetics and Molecular Biology: ASJC main category. - 1400 Business, Management and Accounting: ASJC main category. - 1500 Chemical Engineering: ASJC main category. - 1600 Chemistry: ASJC main category. - 1700 Computer Science: ASJC main category. - 1800 Decision Sciences: ASJC main category. - 1900 Earth and Planetary Sciences: ASJC main category. - 2000 Economics, Econometrics and Finance: ASJC main category. - 2100 Energy: ASJC main category. - 2200 Engineering: ASJC main category. - 2300 Environmental Science: ASJC main category. - 2400 Immunology and Microbiology: ASJC main category. - 2500 Materials Science: ASJC main category. - 2600 Mathematics: ASJC main category. - 2700 Medicine: ASJC main category. - 2800 Neuroscience: ASJC main category. - 2900 Nursing: ASJC main category. - 3000 Pharmacology, Toxicology and Pharmaceutics: ASJC main category. - 3100 Physics and Astronomy: ASJC main category. - 3200 Psychology: ASJC main category. - 3300 Social Sciences: ASJC main category. - 3400 Veterinary: ASJC main category. - 3500 Dentistry: ASJC main category. - 3600 Health Professions: ASJC main category.

The classification in reproducible and not reproducible models was made by Tiwari et al.

Citations were looked up in Scopus, Web of Science and Google Scholar.

The following journals had to be excluded, as Journal Impact Factors (JIF) were missing or papers were discontinued: * Experientia was closed 1996 and continued as Cellular and Molecular Life Sciences 1997 * The American journal of physiology – split into fields 1977, further splits in 1980 and 1989 * IFAC Proceedings Volumes – last issue 2014, continued as IFAC-PapersOnLine * Mathematical and Computer Modelling – discontinued as of 2014 * IOP Conference Series: Materials Science and Engineering – not a journal but conference proceedings – no impact factor listed * Infectious Disease Modelling – no impact factor found * Jurnal Teknologi – no impact factor found * JCO clinical cancer informatics – no impact factor found * Quantitative biology (Beijing, China) – no impact factor found * Letters in Biomathematics – no impact factor found * Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference – no impact factor found * Haemostasis – discontinued; no impact factor found

It was tried to include as many papers as possible.

As the JIF is calculated every year, an average JIF of the Journal Citation Reports from 2014 to 2021 was calculated and used for the analysis. The results do not differ qualitatively if only the JIF of 2021 was used. As the Journal Impact Factor reports belong to Clarivate the JCR data was not uploaded to the repository.

This dataset provides supplementary data extracted and processed from the SCImago Journal Rank portal (2023) and the Scopus Discontinued Titles list (February 2025). It includes journal-level metrics such as SJR and h-index, quartile assignments, and subject category information. The files are intended to support exploratory analysis of citation patterns, disciplinary variations, and structural characteristics of journal evaluation systems. The dataset also contains Python code and visual materials used to examine relationships between prestige metrics and cumulative citation indicators.

Contents:

• Scimago Journal Rank 2023.xlsx – full SJR dataset with quartile and h-index data.
• Q1 journals with h-index below 5 (SJR 2023).xlsx – filtered subset of Q1 journals with low citation impact.
• Relationship between journal h-index and SJR 2023.png – visualization of SJR vs h-index by quartile.
• Scopus Discontinued Titles (Feb 2025) – list of discontinued sources from Scopus used for consistency checks.
• Python script for data processing and visualization.

Big Data and Society Impact Factor 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

This is the full citation details and DOIs for 85 co-published reporting guidelines, together with the citation counts, number of article accesses and journal impact factor for each article and journal. This represents a total of nine research reporting statements, published across 58 journals in biomedicine.

Factors associated with the assessment of publication bias.