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Record W4405456376 · doi:10.3899/jrheum.2024-1091

Dr. Roberts et al reply

2024· letter· fr· W4405456376 on OpenAlexafffundvenueabout
Janet Roberts, J. Mackinnon, Susan Parlee, Volodko Bakowsky, Trudy Taylor, Claire Barber, John G. Hanly, Alexandra Legge

Bibliographic record

VenueThe Journal of Rheumatology · 2024
Typeletter
Languagefr
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsArthritis Research Centre of CanadaUniversity of CalgaryAlberta Health ServicesQueen Elizabeth II Health Sciences CentreCalgary Laboratory ServicesResearch CanadaNova Scotia Health AuthorityDalhousie University
FundersInstitute of Musculoskeletal Health and ArthritisArthritis SocietyCanadian Institutes of Health ResearchQEII Foundation
KeywordsMedicineTriagePhysical therapyRheumatologyMedical physicsPhysical examinationFamily medicineNuclear medicineInternal medicineMedical emergency

Abstract

fetched live from OpenAlex

To the Editor: We thank Dr. Steiman and colleagues1 for their interest and correspondence regarding our recent publication exploring the feasibility of physiotherapy-led rheumatology triage using a standardized triage algorithm.2 The algorithm used in this study relied on the referring providers’ physical examination, laboratory results, and radiographic results, as well as patient-reported questionnaire scores. Those referrals that reached a prespecified threshold score based on this algorithm, without in-person assessment, were triaged as urgent and assessed in clinic by a rheumatologist. This differs from the face-to-face triage performed by extended role practitioners (ERPs) in several other studies that have … Address correspondence to Dr. J.H. Roberts, Division of Rheumatology and Department of Medicine, Queen Elizabeth II Health Sciences Center and Dalhousie University, Nova Scotia Rehabilitation and Arthritis Centre, 1341 Summer Street, Halifax, NS B3H 4K4, Canada. Email: janet3.roberts{at}nshealth.ca.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.292
Teacher spread0.280 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2024
Admission routes4
Has abstractyes

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