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Record W1988775707 · doi:10.1159/000156113

Canada: Public Health Genomics

2008· article· en· W1988775707 on OpenAlexaffabout
Julian Little, Bea De Potter, Judith Allanson, Timothy Caulfield, June Carroll, Brenda J. Wilson

Bibliographic record

VenuePublic Health Genomics · 2008
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversity of TorontoMount Sinai HospitalUniversity of AlbertaChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsPublic healthPopulationSpecialtyMedical geneticsGenetic testingHealth careMedicineNewborn screeningEnvironmental healthFamily medicineEconomic growthNursingPediatricsGeneticsBiology

Abstract

fetched live from OpenAlex

Canada has a diverse population of 32 million people and a universal, publicly funded health care system provided through provincial and territorial health insurance plans. Public health activities are resourced at provincial/territorial level with strategic coordination from national bodies. Canada has one of the longest-standing genetics professional specialty organizations and is one of the few countries offering master's level training designed specifically for genetic counselors. Prenatal screening is offered as part of routine clinical prenatal services with variable uptake. Surveillance of the effect of prenatal screening and diagnosis on the birth prevalence of congenital anomalies is limited by gaps and variations in surveillance systems. Newborn screening programs vary between provinces and territories in terms of organization and conditions screened for. The last decade has witnessed a four-fold increase in requests for genetic testing, especially for late onset diseases. Tests are performed in provincial laboratories or outside Canada. There is wide variation in participation in laboratory quality assurance schemes, and there are few regulatory frameworks in Canada that are directly relevant to genetics testing services or population genetics. Health technology assessment in Canada is conducted by a diverse range of organizations, several of which have produced reports related to genetics. Several large-scale population cohort studies are underway or planned, with initiatives to harmonize their conduct and the management of ethical issues, both within Canada and with similar projects in other countries.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.102
GPT teacher head0.292
Teacher spread0.190 · 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 designNot applicable
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

Citations14
Published2008
Admission routes2
Has abstractyes

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