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Record W4392589454 · doi:10.1016/j.gimo.2024.101378

P479: The Clinician-reported Genetic testing Utility InDEx: A revised tool to quantify genome-wide sequencing utility in neonatal intensive care (C-GUIDE NICU)

2024· article· en· W4392589454 on OpenAlexaff
Lena Dolman, Elise Poole, Joyce Yan, Stephanie Luca, Bowen Xiao, Wendy J. Ungar, Lauren Chad, Martin Offringa, Robin Z. Hayeems

Bibliographic record

VenueGenetics in Medicine Open · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsIntensive careGenetic testingIndex (typography)MedicineComputational biologyComputer scienceBiologyIntensive care medicineGeneticsWorld Wide Web

Abstract

fetched live from OpenAlex

Measuring the clinical utility of genome-wide sequencing (GS) requires tools that extend beyond laboratory performance. Our team previously developed the Clinician-reported Genetic testing Utility InDEx (C-GUIDE) to quantify clinical utility in medical genetics settings. However, with increasing interest in the utility of this technology in other settings, our team is developing modified versions of this tool for use in prenatal, neonatal, and oncology contexts. There is particular interest in the potential for high diagnostic yield and clinical utility in neonatal critical care, where GS can inform diagnostic, prognostic, therapeutic, and palliative decision-making.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0010.001
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 head0.077
GPT teacher head0.372
Teacher spread0.295 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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