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Record W4394921022 · doi:10.1111/hae.15010

International Prophylaxis Study Group (IPSG) haemophilia joint MRI scale version 2.0

2024· letter· en· W4394921022 on OpenAlexaff
Björn Lundin, Nihal Bakeer, Amy L. Dunn, Sridhar Gibikote, Shyamkumar N. Keshava, Rolf Ljung, Olympia Papakonstantinou, Helen Pergantou, Karen Strike, Annette von Drygalski, Ningning Zhang, Paul Babyn, Saunya Dover, Andréa S. Doria

Bibliographic record

VenueHaemophilia · 2024
Typeletter
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoSickKids FoundationMcMaster Children's HospitalMcMaster UniversityHospital for Sick ChildrenRegional Municipality of NiagaraUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineHaemophiliaScale (ratio)Physical therapyPediatricsFamily medicineCartography

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)0.002
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0340.023

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 head0.036
GPT teacher head0.305
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2024
Admission routes1
Has abstractyes

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