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Record W4220828170 · doi:10.1159/000522271

Geographic Distribution, Number, and Types of Papers Published in International Cytopathology Journals in the Last 5.5 Years: A Preliminary Study

2022· article· en· W4220828170 on OpenAlexaboutno aff
Büşra Yaprak Bayrak, Nadir Paksoy

Bibliographic record

VenueActa Cytologica · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and Literary Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCytopathologyMedicineDeveloping countryLibrary scienceCitationImpact factorCytologyFamily medicinePathologyPolitical scienceLawEconomic growth

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to explore the geographic distribution and number of papers published in international and Science Citation Index (SCI)-indexed cytology journals based on their country of origin. MATERIALS AND METHODS: A country-based geographic analysis of studies published over a 5.5-year period from January 2016 to June 2021 in 5 cytopathology journals indexed as SCI and SCI-E with an impact factor higher than 1 (Cancer Cytopathology, Cytopathology, Diagnostic Cytopathology, Acta Cytologica, and CytoJournal) and papers categorized as "original" and "other" was performed. RESULTS: A total of 3,063 papers were found, with 1,466 (47.8%) categorized as "original" papers and 1,597 (52.1%) designated as "other" papers. These papers were submitted from 62 different countries. The five countries with the greatest number of papers were the USA (38.4%), India (16.8%), Japan (7.4%), Italy (5.5%), and Brazil (3.1%). A general subgroup analysis was also performed on the original studies without a country breakdown. Cytomorphological, cytomorphological-immunohistochemical, and molecular assessments compose 38.5%, 45.7%, and 15% of the subgroups, respectively. CONCLUSION: The number of academic papers originating from developing countries in the field of cytopathology has increased in recent years. Although most scientific papers are produced in developed countries, the rate in these countries is much lower than that in some developing countries as the rate of academic growth in developed countries has stabilized. Despite the widespread and sophisticated implementation of cytology in daily practice in Western European countries outside the UK, such as Germany and the Netherlands, and in Scandinavian countries and other developed countries, such as Australia and Canada, these countries rank in the middle to lower end of countries producing cytology papers. Meanwhile, there has been an increase in the number of cytology papers published by authors from Southern European countries, such as Italy (ranked 4th) and Spain (ranked 6th), and Turkey (ranked 8th). There is a remarkable increase in cytology papers originating from Asia, particularly India, Japan, and China. SUMMARY: We aimed to present a basic survey of the geographic distribution of manuscript submissions to high-impact cytopathology journals and to point out emerging trends in cytology utilization and basic research. However, our results show that the landscape of cytology is changing and suggest geographic regions that are ripe for the production of novel "points of view" and new research findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0250.029
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.247
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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