MétaCan
Menu
Back to cohort
Record W2614006244 · doi:10.1038/gim.2017.43

Gene patents still alive and kicking: their impact on provision of genetic testing for long QT syndrome in the Canadian public health-care system

2017· article· en· W2614006244 on OpenAlexafffundabout
Sarah E. Ali‐Khan, E. Richard Gold

Bibliographic record

VenueGenetics in Medicine · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill University
FundersGenome AlbertaOntario Ministry of Health and Long-Term CareGenome Canada
KeywordsBlueprintGenetic testingContext (archaeology)Public healthLong QT syndromeHealth careTest (biology)MedicineBusinessPolitical scienceLawGeographyNursing

Abstract

fetched live from OpenAlex

PurposeAlthough the Supreme Court of the United States limited their availability in Association for Molecular Pathology v. Myriad Genetics, gene patents remain important around the world. We examine the situation in Canada, where gene patents continue to exist, in light of recent litigation relating to familial long QT syndrome (LQTS).MethodsWe conducted in-depth semistructured interviews with 25 stakeholders across five Canadian provinces and supplemented this with a case analysis of the litigation.ResultsThe majority of LQTS testing was carried out outside Canada. Rising costs prompted several provinces to attempt to repatriate testing. However, LQTS gene patents stymied efforts, particularly in provinces where testing was more centralized, increasing costs and lowering innovation. It was in this context that a hospital launched a test case against the LQTS patents, resulting in a novel agreement to free Canadian hospitals from the effects of patents.ConclusionOur analysis reveals a rapidly evolving genetic test provision landscape under pressure from gene patents, strained budgets and poor collaboration. The litigation resulted in a blueprint for free public use of gene patents throughout Canada's health-care system, but it will only have value if governments are proactive in its use.

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)0.013
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0330.012
Scholarly communication0.0120.003
Open science0.0030.008
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.000

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 head0.044
GPT teacher head0.346
Teacher spread0.302 · 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.

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

Citations4
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueGenetics in MedicineSame topicCRISPR and Genetic EngineeringFrench-language works237,207