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Record W4407598057 · doi:10.7759/cureus.79065

Analysis of Obstetrics and Gynecology Residency Program Website Contents in the United States of America

2025· article· en· W4407598057 on OpenAlexaff
Harneet Cheema, Xinyan Li, Mehr Jain, Faisal Khosa

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsVancouver General HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineObstetrics and gynaecologyResidency trainingObstetricsFamily medicineMedical educationGynecologyPregnancyContinuing education

Abstract

fetched live from OpenAlex

Background Obstetrics and gynecology (OB/GYN) residency program websites are essential resources for applicants when selecting a residency program. Assessing these websites against a 58-point criterion can provide program administrators with actionable insights to enhance their content and make them more informative for applicants. Objective This study aims to evaluate the comprehensiveness of content on American OB/GYN residency program websites. Methods We reviewed American OB/GYN residency program websites listed on the Fellowship and Residency Electronic Interactive Database (FRIEDA). A 58-point criterion was developed based on the Accreditation Council for Graduate Medical Education (ACGME) common program requirements and prior studies. The criteria included seven categories. Programs without a webpage, military-based programs, and non-US-based programs were excluded. Results A total of 272 program websites met the inclusion criteria. On average, websites contained only 28 of the 58 study criteria (48.6%). The most commonly included information was the residency manual (59.1%), while details about didactics and program structure were the least commonly included (40.7%). Conclusion The majority of American OB/GYN residency program websites lack comprehensive information for applicants. Residency programs should consider incorporating key details such as application information, introduction to the program, residency manual, didactics and program description, research, current resident information, and graduate/post-residency placement.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0120.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.085
GPT teacher head0.429
Teacher spread0.345 · 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
DomainReporting
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

Citations0
Published2025
Admission routes1
Has abstractyes

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