MétaCan
Menu
Back to cohort
Record W2082209838 · doi:10.1016/j.ypmed.2010.08.005

AGREE II: Advancing guideline development, reporting, and evaluation in health care

2010· article· en· W2082209838 on OpenAlexafffund
Melissa Brouwers, Michelle E. Kho, George P. Browman, Jako Burgers, Françoise Cluzeau, Gene Feder, Béatrice Fervers, Ian D. Graham, Jeremy Grimshaw, Steven Hanna, Peter Littlejohns, Julie Makarski, Louise Zitzelsberger

Bibliographic record

VenuePreventive Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCanadian Partnership Against CancerBC Cancer AgencyOttawa HospitalCanadian Institutes of Health ResearchCancer Care OntarioMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicineGuidelineScale (ratio)Key (lock)Health careMedical educationComputer sciencePathology

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)0.494
metaresearch head score (Gemma)0.670
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: none
Teacher disagreement score0.506
Threshold uncertainty score0.625

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4940.670
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0120.010
Science and technology studies0.0050.005
Scholarly communication0.0170.010
Open science0.0110.024
Research integrity0.0180.021
Insufficient payload (model declined to judge)0.0110.005

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 head0.195
GPT teacher head0.551
Teacher spread0.355 · 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

Citations772
Published2010
Admission routes2
Has abstractno

Explore more

Same venuePreventive MedicineSame topicClinical practice guidelines implementationFrench-language works237,207