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Record W2012641675 · doi:10.1159/000051118

From Family to Pharmacogenetics

2000· article· en· W2012641675 on OpenAlexaffabout
Pavel Hamet, Daniel Gaudet, Gérard Bouchard, Zdenka Pausová, Johanne Tremblay, Michèle Jomphe, Pierre Larochelle, G Tremblay, Theodore A. Kotchen, Allen W. Cowley, Françis Gossard

Bibliographic record

VenuePublic Health Genomics · 2000
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsCégep de ChicoutimiCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsHeritabilityHeredityPhenotypePharmacogeneticsPopulationTraitGeneticsMedicineBiologyQuantitative trait locusGenotypeGene

Abstract

fetched live from OpenAlex

Hypertension is a complex disease in which environment and heredity interact. It is a polygenic trait that can be studied by investigating its intermediate phenotypes. We have selected the population from the Saguenay-Lac St. Jean region because it is a relative genetic isolate. We have found that the prevalence of hypertension at every age level was greater than in a control Canadian population. A sib pair analysis was used to measure familial correlation and heritability of more than 200 phenotypes among which were renal functions, anthropometric measures and cardiac morphology and reactivity. Very strong familial correlations were estimated for several cardiovascular phenotypes. During a pharmacological infusion of norepinephrine, we observed that systolic blood pressure was increased as expected but that the heritable component of this phenotype increased from null at baseline to close to 70%. Preliminary total genome scans completed on the DNA of the participants have selected several regions linked to these phenotypes. This type of study opens the door to pharmacogenetic studies in which sib pairs are analyzed for their concordant or discordant response to a medication.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.099
GPT teacher head0.348
Teacher spread0.249 · 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 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

Citations0
Published2000
Admission routes2
Has abstractyes

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