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Strengthening the reporting of genetic association studies (STREGA)—an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

2009· article· en· W1988176578 on OpenAlexaff
Julian Little, Julian P. T. Higgins, John P. A. Ioannidis, David Moher, France Gagnon, Erik von Elm, Muin J. Khoury, Barbara Cohen, Jeremy Grimshaw, Paul Scheet, Marta Gwinn, Robin E. Williamson, Guangyong Zou, Kim Hutchings, Candice Y. Johnson, Valerie Tait, Miriam Wiens, Jean Golding, Cornelia M. van Duijn, John McLaughlin, Andrew D. Paterson, George A. Wells, Isabel Fortier, Matthew L. Freedman, Maja Zečević, Richard King, Claire Infante-Rivard, Alexandre F.R. Stewart, Nick Birkett

Bibliographic record

VenueJournal of Clinical Epidemiology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityCancer Care OntarioLunenfeld-Tanenbaum Research InstituteRobarts Clinical TrialsWestern UniversityMcGill University and Génome Québec Innovation CentrePublic Health OntarioSickKids FoundationUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsObservational studyStrengthening the reporting of observational studies in epidemiologyStatement (logic)EpidemiologyAssociation (psychology)MedicineExtension (predicate logic)MEDLINEFamily medicineEnvironmental healthActuarial sciencePsychologyComputer scienceBusinessPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.840
metaresearch head score (Gemma)0.903
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.160
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8400.903
Meta-epidemiology (narrow)0.0040.010
Meta-epidemiology (broad)0.0180.025
Bibliometrics0.0200.026
Science and technology studies0.0060.013
Scholarly communication0.0150.010
Open science0.0170.032
Research integrity0.0300.038
Insufficient payload (model declined to judge)0.0050.005

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 head0.498
GPT teacher head0.545
Teacher spread0.047 · 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

Citations102
Published2009
Admission routes1
Has abstractno

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