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Record W2588891160 · doi:10.1186/s13033-017-0127-5

Worldwide research productivity in the field of psychiatry

2017· article· en· W2588891160 on OpenAlexaboutno aff
Jinghua Zhang, Xiaoou Chen, Xin Gao, Huizeng Yang, Zhen Zhong, Qingwei Li, Yiqun Lin, Xiyan Zhao

Bibliographic record

VenueInternational Journal of Mental Health Systems · 2017
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersChinese People’s Liberation Army
KeywordsProductivityPopulationPer capitaGeographyDemographyPsychiatryMedicineEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: The field of psychiatry has seen significant progress in recent years due to worldwide contributions. National productivity, however, in the field of psychiatry is still unclear. In our study, we investigated contributions of individual nations to the field of psychiatry. METHODS: The Web of Science was used to perform a search from 2011 to 2015 on the subject category "psychiatry". The total number of articles, citations and the per capita numbers were obtained to analyze the contributions of different countries. RESULTS: In psychiatry journals from 2011 to 2015, 84,760 articles were published worldwide. The most productive world areas were North America, East Asia, Europe and Oceania. The percentage of articles published in high-income countries was 87.77%, middle-income countries published 12.07%, and lower-income published 0.16%. Most articles were published by the United States (32.68%); the United Kingdom was next (8.59%), which was followed by Germany (6.77%), Australia (5.87%), and Canada (4.9%). The country with the highest number of citations (243,394) was the United States. A positive correlation was found between the population/GDP and the number of publications (P < 0.01). Australia ranked the highest when normalized to population size, and the Netherlands and Norway were next. The Netherlands ranked highest, followed by Israel and Australia when adjusted for GDP. CONCLUSIONS: The authorship of most of the psychiatry articles was from high-income countries and few papers came from low-income countries. The most productive country was the United States. However, when normalized to population size and GDP, some European and Oceania countries were most productive.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.116
GPT teacher head0.549
Teacher spread0.433 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations61
Published2017
Admission routes1
Has abstractyes

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