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Record W4394305186 · doi:10.6084/m9.figshare.19687031

Additional file 1 of Pathogenic variants carrier screening in New Brunswick: Acadians reveal high carrier frequency for multiple genetic disorders

2022· dataset· en· W4394305186 on OpenAlexaffabout
Philippe Pierre Robichaud, Éric P. Allain, Sarah Belbraouet, Claude Bhérer, Jean Mamelona, Jason Harquail, Stéphanie Crapoulet, Nicolas Crapoulet, Mathieu Bélanger, Mouna Ben Amor

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversité de SherbrookeAtlantic Cancer Research InstituteVitalité Health NetworkUniversité de MonctonMcGill UniversityDr. Georges-L.-Dumont University Hospital Centre
Fundersnot available
KeywordsCarrier signalGeneticsBiologyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Additional file 1. Table S1. Genes included in sequencing panel. Table S2. Cohort characteristics. Table S3. Genetic diseases associated with genes in which pathogenic variants have been detected. Table S4. Allele frequency (AF) and heterozygotes frequencies (HF) comparisons with higher risk populations on gnomAD. Table S5. Hardy-Weinberg comparison.

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)0.001
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.974
Threshold uncertainty score0.819

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4260.062

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 head0.027
GPT teacher head0.311
Teacher spread0.284 · 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.

Study designObservational
Domainnot available
GenreDataset

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
Published2022
Admission routes2
Has abstractyes

Explore more

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