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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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.060
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 teacher head, not a consensus.

Study designOther design
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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