MétaCan
Menu
Back to cohort
Record W2136226268 · doi:10.2217/pgs.12.204

Institutional Profile: The Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre at the Montreal Heart Institute

2013· article· en· W2136226268 on OpenAlexaffabout
Marie‐Pierre Dubé, Jean‐Claude Tardif

Bibliographic record

VenuePharmacogenomics · 2013
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsPharmacogenomicsExcellenceCenter of excellenceGeneral partnershipCommercializationBest practiceLibrary scienceMedicineManagementEngineering managementEngineeringPolitical scienceComputer sciencePharmacology

Abstract

fetched live from OpenAlex

The Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre (Québec, Canada) is an academic organization dedicated to advancing knowledge and promoting discoveries in personalized medicine by leading high-quality pharmacogenomic research in partnership with industrial, governmental and academic organizations. Since its establishment in 2008, the Centre has been leading innovative genomics research programs for all phases of drug development and has conducted over 120 pharmacogenomic projects through collaborations with international partners using state-of-the-art platforms with the highest-quality data. The Centre has a fully equipped DNA and genomic laboratory facility, supported by bioinformatics, statistical genetics, quality assurance and project management teams. More recently, the Centre has partnered with the Centre of Excellence in Personalized Medicine for the commercialization of biomarkers and implementation in clinical practice, and with the Montreal Health Innovations Coordinating Centre for study coordination and integration with drug development pipelines. Through its academic excellence, unique expertise in Canada and international industrial partners, the Pharmacogenomics Centre is providing the technologies and research discoveries needed to provide the right therapy to the right patients.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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 teacher head, not a consensus.

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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venuePharmacogenomicsSame topicLipoproteins and Cardiovascular HealthFrench-language works237,207