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Record W2762890992 · doi:10.5014/ajot.2017.023747

Highly Cited Occupational Therapy Articles in the Science Citation Index Expanded and Social Sciences Citation Index: A Bibliometric Analysis

2017· article· en· W2762890992 on OpenAlexaboutno aff
Ted Brown, Sharon A. Gutman, Yuh‐Shan Ho, Kenneth N. K. Fong

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCitation indexCitationScience Citation IndexIndex (typography)BibliometricsSocial Sciences Citation IndexMedicineCitation analysisLibrary scienceSocial scienceSociologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: A bibliometric analysis was completed of highly cited occupational therapy literature and authors published from 1991 to 2014 and accessible in the Science Citation Index Expanded (SCI-Expanded) and Social Sciences Citation Index (SSCI) databases. METHOD: Data were obtained from the SCI-Expanded and SSCI. Articles referenced >100 times were categorized as highly cited articles (HCA). RESULTS: Of 6,486 articles found, 31 were categorized as HCA. The American Journal of Occupational Therapy published the largest number of HCA (n = 8; 26%). The 31 HCA were distributed across seven countries: United States (20 articles), Canada (3), United Kingdom (3), Australia (2), the Netherlands (1), New Zealand (1), and Sweden (1). The three authors with the highest Y-index were S. J. Page, F. Clark, and W. Dunn. CONCLUSION: A latency period of 4 to 5 yr post-publication appears to be needed for a journal article to gain citations.

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)0.015
metaresearch head score (Gemma)0.080
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 score0.815
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.080
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.1850.174
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.348
GPT teacher head0.552
Teacher spread0.204 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Occupational TherapySame topicOccupational Therapy Practice and ResearchFrench-language works237,207