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Record W2669932351 · doi:10.1007/s11926-017-0666-4

Framework for Advancing the Reporting of Patient Engagement in Rheumatology Research Projects

2017· review· en· W2669932351 on OpenAlexafffund
Clayon B. Hamilton, Jenny Leese, Alison M. Hoens, Linda Li

Bibliographic record

VenueCurrent Rheumatology Reports · 2017
Typereview
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsArthritis Research Centre of CanadaResearch CanadaUniversity of British Columbia
FundersEuropean League Against RheumatismMichael Smith Health Research BC
KeywordsMedicineRheumatologyInternal medicineOutcomes researchMedical educationScope (computer science)Rheumatoid arthritisQuality (philosophy)Alternative medicineFamily medicineComputer 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)0.437
metaresearch head score (Gemma)0.539
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: Review · Consensus signal: Review
Teacher disagreement score0.563
Threshold uncertainty score0.694

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4370.539
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0290.022
Science and technology studies0.0060.010
Scholarly communication0.0250.015
Open science0.0120.026
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0080.003

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 head0.747
GPT teacher head0.639
Teacher spread0.108 · 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
GenreReview

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

Citations44
Published2017
Admission routes2
Has abstractno

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