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Record W4200090760 · doi:10.11124/jbies-21-00099

The Functional Resonance Analysis Method as a health care research methodology: a scoping review

2021· review· en· W4200090760 on OpenAlexaff
Alexis McGill, Doug Smith, Rose McCloskey, Patricia Morris, Alex Goudreau, Brian Veitch

Bibliographic record

VenueJBI Evidence Synthesis · 2021
Typereview
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsUniversity of New BrunswickHorizon Health NetworkMemorial University of Newfoundland
Fundersnot available
KeywordsHealth carePsychologyManagement scienceMedicineEngineeringPolitical science

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.151
metaresearch head score (Gemma)0.292
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.849
Threshold uncertainty score0.799

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1510.292
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0090.007
Bibliometrics0.0660.048
Science and technology studies0.0050.007
Scholarly communication0.0140.015
Open science0.0050.007
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0080.002

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 head0.383
GPT teacher head0.616
Teacher spread0.233 · 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.

Study designSystematic review
DomainMethods
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

Citations33
Published2021
Admission routes1
Has abstractyes

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