MétaCan
Menu
Back to cohort
Record W1976405649 · doi:10.1016/j.carj.2009.05.009

Things that go Bump in the Body: Musculoskeletal Sports Medicine Magnetic Resonance Imaging Cases: Part 2 of 2

2009· article· en· W1976405649 on OpenAlexaffabout
David A. Leswick, Joanna Davidson, G.W. Bock, Paul A. Major, Bruce Maycher

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsResearch ManitobaHealth Sciences CentreUniversity of SaskatchewanPan Am ClinicSt. Boniface HospitalRoyal University Hospital
Fundersnot available
KeywordsMedicineFamily medicineMagnetic resonance imagingGerontologyRadiology

Abstract

fetched live from OpenAlex

Department of Medical Imaging, University of Saskatchewan, Royal University Hospital, Saskatoon, Saskatchewan, Canada Pan Am Medical Clinic, Winnipeg, Manitoba, Canada Department of Radiology, Health Sciences Centre, Winnipeg, Manitoba, Canada C/o The Radiology Consultants of Winnipeg, Winnipeg, Manitoba, Canada Department of Diagnostic Imaging, St Boniface General Hospital, Winnipeg, Manitoba, Canada Canadian Association of Radiologists Journal 60 (2009) 248e262 www.carjonline.org

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.003
Science and technology studies0.0040.003
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0210.005

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 head0.015
GPT teacher head0.285
Teacher spread0.270 · 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 designCase report
Domainnot available
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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Association of Radiologists JournalSame topicShoulder Injury and TreatmentFrench-language works237,207