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Record W4379259672 · doi:10.1136/bmjopen-2023-072999

Two-step offer and return of multiple types of additional genomic findings to families after ultrarapid trio genomic testing in the acute care setting: a study protocol

2023· article· en· W4379259672 on OpenAlexaff
Sophie E. Bouffler, Ling Lee, Fiona Lynch, Melissa Martyn, Elly Lynch, Ivan Macciocca, Lisette Curnow, Giulia McCorkell, Sebastian Lunke, Belinda Chong, Justine E. Marum, Martin B. Delatycki, Lilian Downie, Ilias Goranitis, Danya F. Vears, Stephanie Best, Marc Clausen, Yvonne Bombard, Zornitza Stark, Clara Gaff

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersNational Health and Medical Research CouncilAustralian Genomics Health AllianceState Government of VictoriaAustralian GovernmentU.S. Department of Health and Human ServicesChildren's Hospital FoundationRoyal Children's Hospital FoundationMedical Research CouncilChildren’s Hospital of Wisconsin Research InstituteMurdoch Children's Research Institute
KeywordsMedicineGenetic testingProtocol (science)Family medicineGenetic counselingInformed consentHealth careTest (biology)Research ethicsGenomic medicineQualitative researchAlternative medicinePathologyPsychiatryGenetics

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)0.087
metaresearch head score (Gemma)0.049
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.087
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.049
Meta-epidemiology (narrow)0.0030.005
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0030.003
Science and technology studies0.0080.004
Scholarly communication0.0050.007
Open science0.0070.006
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0660.022

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 head0.030
GPT teacher head0.346
Teacher spread0.316 · 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
GenreProtocol

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

Citations11
Published2023
Admission routes1
Has abstractyes

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