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Record W1974967370 · doi:10.1159/000086758

Demogenetic Study of Three Populations within a Region with Strong Founder Effects

2005· article· en· W1974967370 on OpenAlexafffundabout
Ève-Marie Lavoie, Marc Adélard Tremblay, Louis Houde, Hélène Vézina

Bibliographic record

VenuePublic Health Genomics · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversité du Québec à Chicoutimi
FundersSocial Sciences and Humanities Research Council of CanadaUniversité du Québec à ChicoutimiUniversité Laval
KeywordsFounder effectKinshipInbreedingDemographyPopulationGeographyDemographic historyGenealogyBiologyHistoryGenetic variationGeneticsAnthropologyHaplotypeSociologyGenotype

Abstract

fetched live from OpenAlex

OBJECTIVES: The population of the Saguenay-Lac-St-Jean (SLSJ) region (Quebec, Canada) is known to have a relatively high prevalence of certain hereditary disorders, which can be explained by the consequences of founder effects. This study aims at providing new insights on the origins and subregional stratification of these founder effects. METHODS: The genealogies of 300 individuals were reconstructed and analyzed using the BALSAC population register. RESULTS: Inbreeding and kinship levels are higher in Lower Saguenay than in Upper Saguenay and Lac-St-Jean. The population of Lower Saguenay also distinguishes itself because of a fewer number of distinct ancestors. CONCLUSION: Beyond the genetic features that characterize the whole region, SLSJ also displays intraregional variability. Thus it is important to take into account the settlement patterns and the demographic history of this population for a better appraisal of its contemporary genetic structure.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.338
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 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

Citations27
Published2005
Admission routes3
Has abstractyes

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