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Record W2535322980 · doi:10.2217/pgs-2016-0092

Addressing Ethical Challenges at the Intersection of Pharmacogenomics and Primary Care Using Deliberative Consultations

2016· article· en· W2535322980 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePharmacogenomics · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of GuelphMcGill University
FundersCanadian Institutes of Health ResearchPublic Health Agency of CanadaGenome CanadaMcGill UniversityGenomic Health
KeywordsPharmacogenomicsIntersection (aeronautics)Primary careMedicinePsychologyPharmacologyFamily medicineGeography

Abstract

fetched live from OpenAlex

AIM: Primary care physicians will play a central role in the successful implementation of pharmacogenomics (PGx); however, important challenges remain. We explored the perspectives of stakeholders on key challenges of the PGx translation process in primary care using deliberative consultations. METHODS: Primary care physicians, patients and policy-makers attended deliberations, where they discussed four ethical questions raised by PGx research and implementation in the primary care context. RESULTS: Stakeholders voiced skepticism regarding PGx funding, commercialization, regulation, maintenance of an equal access healthcare system and restructuring of health research incentives and priorities in the public sector. CONCLUSION: Deliberants developed governing principles for a PGx-specific charter of ethics, aiming to protect the interests of patients, and outlined recommendations for the future of PGx in primary care.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.313
GPT teacher head0.471
Teacher spread0.158 · 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