Association mapping of genes using whole genome polymorphism arrays: Identification of markers of breast cancer susceptibility in Alberta women
Bibliographic record
Abstract
Breast cancer is a heterogeneous, polygenic disease and is influenced by genetic, environmental and life-style factors. Many single nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified in genome-wide association studies (GWASs) by several research groups for different populations. However, the variants identified so far contribute to a small proportion of disease risk. The objectives of the work described in this thesis were (i) to seek relevance/replicability of reported risk alleles from SNP scans to our study population; and (ii) to perform an independent GWAS for identification of additional/novel polymorphisms in the Albertan population. We approached these two end points by using cases and controls recruited in Alberta (total sample size, n=3064) in a two-stage association study (discovery study followed by replication study). We reproduced 14 of the 28 variants reported by others and also identified seven novel variants associated with breast cancer risk in our study population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".