MétaCan
Menu
Back to cohort
Record W2138435168 · doi:10.5195/ijms.2014.76

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) in the International Journal of Medical Students

2014· article· en· W2138435168 on OpenAlexaff
Aisha Gharaibeh, Sahil Koppikar, Francisco J. Bonilla‐Escobar

Bibliographic record

VenueInternational Journal of Medical Students · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsQueen's University
Fundersnot available
KeywordsObservational studyStrengthening the reporting of observational studies in epidemiologyEpidemiologyMedicineMedical educationPathology

Abstract

fetched live from OpenAlex

NA

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)0.769
metaresearch head score (Gemma)0.926
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.231
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7690.926
Meta-epidemiology (narrow)0.0040.010
Meta-epidemiology (broad)0.0200.030
Bibliometrics0.0180.020
Science and technology studies0.0050.013
Scholarly communication0.0200.014
Open science0.0090.019
Research integrity0.0210.021
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 head0.861
GPT teacher head0.677
Teacher spread0.184 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations46
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Medical StudentsSame topicMeta-analysis and systematic reviewsFrench-language works237,207