MétaCan
Menu
Back to cohort
Record W3130678172 · doi:10.1016/j.jmoldx.2021.01.014

Harmonizing the Collection of Clinical Data on Genetic Testing Requisition Forms to Enhance Variant Interpretation in Hypertrophic Cardiomyopathy (HCM)

2021· article· en· W3130678172 on OpenAlexaff
Ana Morales, Alexander Ing, Christian Antolik, Christina Austin‐Tse, Linnea M. Baudhuin, Lucas Bronicki, Allison L. Cirino, Megan Hawley, Michael Fietz, John Garcia, Carolyn Y. Ho, Jodie Ingles, Olga Jarinova, Tami Johnston, Melissa Kelly, C. Lisa Kurtz, Matthew S. Lebo, Daniela Macaya, Lisa Mahanta, Joseph J. Maleszewski, Arjun K. Manrai, Mitzi L. Murray, Gabriele Richard, Chris Semsarian, Kate Thomson, Tom Winder, James S. Ware, Ray E. Hershberger, Birgit Funke, Matteo Vatta

Bibliographic record

VenueJournal of Molecular Diagnostics · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
FundersNational Institute of Child Health and Human DevelopmentNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentMyoKardiaWellcome Trust
KeywordsRequisitionHypertrophic cardiomyopathyMedicineData miningComputer scienceInternal medicineGeography

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 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)0.001
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.361
Teacher spread0.287 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Molecular DiagnosticsSame topicCardiomyopathy and Myosin StudiesFrench-language works237,207