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Record W2169202956 · doi:10.1126/scitranslmed.3008494

Whole-Genome Sequencing in Newborn Screening Programs

2014· article· en· W2169202956 on OpenAlexaff
Bartha Maria Knoppers, Karine Sénécal, Pascal Borry, Denise Avard

Bibliographic record

VenueScience Translational Medicine · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsWhole genome sequencingGenomeNewborn screeningComputational biologyDNA sequencingBiologyMedicineGeneticsDNAGene

Abstract

fetched live from OpenAlex

The availability of whole-genome sequencing (WGS) is likely to change the practice of population screening programs such as newborn screening (NBS). This Commentary raises key ethical, legal, and social issues surrounding WGS in NBS and suggests a need for deliberation regarding the policy challenges of introducing sequencing in such programs. Any change in the goals of NBS programs should be discussed carefully and should represent the best interests of the child.

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)0.061
metaresearch head score (Gemma)0.138
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.138
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0040.006
Open science0.0030.004
Research integrity0.0260.020
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.272
Teacher spread0.250 · 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 designTheoretical or conceptual
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

Citations86
Published2014
Admission routes1
Has abstractyes

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