MétaCan
Menu
Back to cohort
Record W2773345223 · doi:10.1002/art.40321

Validation of Online Calibration Modules for the Spondyloarthritis Research Consortium of Canada MRI Scores Based on Real-Time Experiential Learning

2017· article· en· W2773345223 on OpenAlexaffabout
M. P. Maksymowych, H. Boutrup, Jonathan T. L. Cheah, Riccardo Guglielmi, Eric Heffernan, Jacob L. Jaremko, Mats Peter Johansson, Simon Krabbe, Georg Kröber, Fardina Malik, Susanne Juhl Pedersen, Sander Shafer, Ulrich Weber, Pam Weiss, Brian Trinh, Joel Paschke, R. Lambert

Bibliographic record

VenueUniversity of Southern Denmark Research Portal (University of Southern Denmark) · 2017
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCalibrationExperiential learningMedicineMedical physicsPhysical therapyComputer sciencePsychologyStatisticsMathematicsPedagogy

Abstract

fetched live from OpenAlex

Background/Purpose: The appropriate use of imaging-based scoring instruments is usually an ad hoc process based on passive learning from published manuscripts. Moreover, most instruments lack knowledge transfer tools that would facilitate attainment of pre-specified performance targets for reader reliability prior to use in clinical trials and research. We aimed to develop and validate online calibration […]

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations8
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of Southern Denmark Research Portal (University of Southern Denmark)Same topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207