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Record W4386553228 · doi:10.21203/rs.3.rs-3314629/v1

Evaluation of an integrated knowledge translation approach used for updating the Cochrane Review of Patient Decision Aids

2023· preprint· en· W4386553228 on OpenAlexafffund
Krystina B. Lewis, Maureen Smith, Dawn Stacey, Meg Carley, Ian D. Graham

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsOttawa HospitalCochraneUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsKnowledge translationPsychologyDecision aidsSystematic reviewApplied psychologyScale (ratio)Medical educationBaseline (sea)Computer scienceMEDLINEMedicineKnowledge managementAlternative medicinePolitical science

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)0.321
metaresearch head score (Gemma)0.595
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3210.595
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0090.013
Bibliometrics0.0160.020
Science and technology studies0.0020.002
Scholarly communication0.0110.008
Open science0.0050.009
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0200.002

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 head0.717
GPT teacher head0.632
Teacher spread0.085 · 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 designObservational
DomainEvaluation
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

Citations1
Published2023
Admission routes2
Has abstractno

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