MétaCan
Menu
Back to cohort

Understanding the Relevance of Measured Change Through Studies of Responsiveness

2000· review· en· W2053496236 on OpenAlexaffabout
Dorcas E. Beaton

Bibliographic record

VenueSpine · 2000
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsMedicineReprintWork (physics)Relevance (law)Public healthMedical educationLibrary scienceGerontologyFamily medicineNursing

Abstract

fetched live from OpenAlex

From the Institute for Work and Health, Department of Occupational Therapy, and Clinical Epidemiology and Health Services Research Program, University of Toronto, Toronto, Ontario, Canada. Address reprint requests to Dorcas E. Beaton, BScOT, MSc, PhD Institute for Work & Health 250 Bloor St., Suite 702 Toronto, ON, M4W 1E6 Canada E-mail: [email protected] DB was supported by a PhD Fellowship (health research) from the Medical Research Council of Canada during the period of this research. This work was also supported in part by the Institute for Work and Health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.042
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.042
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.118
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0060.007
Science and technology studies0.0000.004
Scholarly communication0.0040.007
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.369
GPT teacher head0.438
Teacher spread0.069 · 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 designSystematic review
Domainnot available
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

Citations355
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueSpineSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207