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Record W4392606809 · doi:10.1016/j.gimo.2024.101441

P542 :Twenty years of newborn and carrier screening in the Old Order Amish population of Southwestern Ontario: Evolution and evaluation

2024· article· en· W4392606809 on OpenAlexaffabout
Jamie A. Abbott, Emma Reesor, Jane Leach, Cynthia Soulliere, Wendy McCaul, Anthony Rupar, Victoria Mok Siu

Bibliographic record

VenueGenetics in Medicine Open · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsWestern UniversityLondon Health Sciences CentreMcMaster University
Fundersnot available
KeywordsOrder (exchange)DemographyGenealogyPopulationGerontologyGeographyMedicineHistorySociologyEconomics

Abstract

fetched live from OpenAlex

Southwestern Ontario has the largest population of Old Order Amish (OOA) in Canada, consisting of about 370 families who live in closed rural communities, are geographically and culturally isolated, and have a gene pool originating from 12 founding couples. Their genetic disorders are distinct from those seen in the United States. This population opts out of Canadian universal healthcare. In 2003, we began targeted variant newborn screening for 4 treatable genetic disorders. Provision of testing locally was essential to avoid transportation costs for this horse-and-buggy population.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.293
Teacher spread0.254 · 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 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 routes2
Has abstractyes

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