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Record W4211117352 · doi:10.1038/s41436-019-0521-2

Correction: Genetic evaluation of cardiomyopathy: a clinical practice resource of the American College of Medical Genetics and Genomics(ACMG)

2019· erratum· en· W4211117352 on OpenAlexaff
Ray E. Hershberger, Michael M. Givertz, Carolyn Y. Ho, Daniel P. Judge, Paul F. Kantor, Kim L. McBride, Ana Morales, Matthew R.G. Taylor, Matteo Vatta, Stephanie M. Ware

Bibliographic record

VenueGenetics in Medicine · 2019
Typeerratum
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsStollery Children's Hospital
Fundersnot available
KeywordsGuidelineMedical geneticsCardiomyopathySection (typography)Resource (disambiguation)MedicineStatement (logic)Clinical PracticeFamily medicineHeart failureCardiologyGeneticsComputer sciencePolitical sciencePathologyBiologyLaw

Abstract

fetched live from OpenAlex

In the original version of this Article, the Statement on Conflict of Interest originally submitted by the authors was not published. Furthermore, in the Acknowledgements section we neglected to state that this article is an abbreviated version of "Genetic Evaluation of Cardiomyopathy—a Heart Failure Society oF.A.merica Practice Guideline," published in Journal of Cardiac Failure . The PDF.A.nd HTML versions of the Article have now been corrected.

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)0.005
metaresearch head score (Gemma)0.118
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.102
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.118
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.1020.047

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 head0.051
GPT teacher head0.392
Teacher spread0.341 · 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
GenreEditorial

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

Citations6
Published2019
Admission routes1
Has abstractyes

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