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Record W4392588856 · doi:10.1016/j.gimo.2024.101426

P527: Evidence-based methodology for developing coordinated genetic service recommendations in Ontario

2024· article· en· W4392588856 on OpenAlexaffabout
Luis de la Peña, Angela Du, Kaitlyn Lemay, Kathleen Bell, Raymond Kim

Bibliographic record

VenueGenetics in Medicine Open · 2024
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity Health Network
Fundersnot available
KeywordsService (business)Process managementComputer scienceBusinessMarketing

Abstract

fetched live from OpenAlex

The field of genetics has rapidly evolved, revealing that rare and inherited diseases are collectively common. To address the challenges posed by this large patient population for the local healthcare system, the Provincial Genetics Program (PGP) at Ontario Health (OH) is developing recommendations for the delivery of services and implementation of testing for individuals with hereditary cancer, rare and inherited diseases. Following an evidence-based framework, the guidance documents aim to enhance patient access and clinical services by offering standardized, coordinated, and comprehensive strategies for physicians involved in diagnosing and/or treating individuals with a genetic condition.

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)0.244
metaresearch head score (Gemma)0.436
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.935
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2440.436
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0130.013
Science and technology studies0.0040.003
Scholarly communication0.0080.003
Open science0.0070.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0130.001

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 head0.806
GPT teacher head0.622
Teacher spread0.184 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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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