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Record W2978368287 · doi:10.3390/ijns5040037

Newborn Screening: Current Status in Alberta, Canada

2019· review· en· W2978368287 on OpenAlexaffabout
Vanessa Wolan, A. R. Battochio, Susan Christian, Stacey Hume, Grace Johner, Margaret Lilley, Ross Ridsdale, Kareena Schnabl, Chi Thanh Tran, Jolene Yuen-Jung, Iveta Sosova

Bibliographic record

VenueInternational Journal of Neonatal Screening · 2019
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsAlberta Health ServicesUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsNewborn screeningMedicinePediatricsCystic fibrosisMetabolic diseaseEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Newborn screening (NBS) in Alberta is delivered by a number of government and health service entities who work together to provide newborn screening to infants born in Alberta, the Northwest Territories, and the Kitikmeot region of the Nunavut territory. The Alberta panel screens for 21 disorders (16 metabolic, two endocrine, cystic fibrosis, severe combined immunodeficiency, and sickle cell disease). NBS is a standard of care, but is not mandatory. NBS performance is monitored by the Alberta Newborn Metabolic Screening (NMS) Program and NMS Laboratory, who strive for continuous quality improvement. Performance analysis found that over 99% of registered infants in Alberta received a newborn screen and over 98% of these infants received a screen result within 10 days of age.

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)0.002
metaresearch head score (Gemma)0.004
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: Review · Consensus signal: Review
Teacher disagreement score0.583
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.060
GPT teacher head0.394
Teacher spread0.334 · 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
GenreReview

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

Citations12
Published2019
Admission routes2
Has abstractyes

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Same venueInternational Journal of Neonatal ScreeningSame topicCystic Fibrosis Research AdvancesFrench-language works237,207