MétaCan
Menu
Back to cohort
Record W4221134303 · doi:10.1007/s00404-022-06453-z

Choosing Wisely Canada: Canadian fertility and andrology society’s list of top items physicians and patients should question in fertility medicine

2022· article· en· W4221134303 on OpenAlexaffabout
Claire Jones, Lesley Hawkins, Catherine L. Friedman, Jason Hitkari, Eileen McMahon, Karen Born

Bibliographic record

VenueArchives of Gynecology and Obstetrics · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsOttawa Fertility CentreUniversity of British ColumbiaMcMaster UniversityHumber River Regional HospitalSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsFertilityMedicinePsychological interventionHarmInfertilityContext (archaeology)Family medicineFertility clinicDelphi methodGynecologyReproductive medicineMEDLINEPregnancyNursingPopulationPsychologyEnvironmental healthSocial psychology

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0090.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0230.004

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 head0.196
GPT teacher head0.415
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2022
Admission routes2
Has abstractno

Explore more

Same venueArchives of Gynecology and ObstetricsSame topicHealthcare cost, quality, practicesFrench-language works237,207