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Record W4324116879 · doi:10.1016/j.gimo.2023.100411

P375: Fragmented systems of care: An overview of Canadian health system care models for hereditary cancer syndromes

2023· article· en· W4324116879 on OpenAlexaffabout
Jordan Sam, Carly Butkowsky, Marc Clausen, Chloe Mighton, Sepideh Rajeziesfahani, Ridhi Gopalakrishnan, Melyssa Aronson, Derrick Bishop, Lesa Dawson, Andrea Eisen, Tracy Graham, Jane Green, Julee Pauling, Claudia Pavao, Catriona Remocker, Sevtap Savas, Sophie Sun, Teresa Tiano, Angelina Tilley, Kevin E. Thorpe, Kasmintan A. Schrader, Holly Etchegary, Yvonne Bombard

Bibliographic record

VenueGenetics in Medicine Open · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreMemorial University of NewfoundlandUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineCancerHealthcare systemHealth carePolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

Hereditary cancer syndromes (HCS) are one of the most prevalent inherited diseases, accounting for 5-10% of all cancers. Patients and their family members with a confirmed genetic diagnosis of a HCS require lifelong screening and follow up since they have an increased risk for multiple malignancies in several organ systems. However, there is limited data on the accessibility and coordination of HCS care across different health jurisdictions in Canada. The purpose of this study is to compare the systems of HCS care in 3 provinces in Canada to support a team grant that aims to explore the indirect socioeconomic and psychosocial impacts of HCS.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.018
Science and technology studies0.0080.004
Scholarly communication0.0050.002
Open science0.0030.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.112
GPT teacher head0.399
Teacher spread0.287 · 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 designSystematic review
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

Citations0
Published2023
Admission routes2
Has abstractyes

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