Genetic hyper-coagulation predisposition for myocardial infarction in the Newfoundland population
Bibliographic record
Abstract
Studies associating prothrombin G20210A (FIIG20210A), Factor V Lei den (FVL), and Factor XIIIV34L (FXIII-A V34L), Factor VII R353Q (FVII R353Q), 5, 10-Methylenetetrahydrofolate reductase A1298C (MTHFR A1298C), and Interleukin-6 -174 G/C (Il-6 -174 G/C) with myocardial infarction (MI) have yielded conflicting results. Complicated gene-gene interactions, small sample sizes and heterogeneous genetic and environmental backgrounds may contribute to conflicting results. Simultaneous analysis of multiple gene variants in a large sample size from a genetically isolated population may overcome these weaknesses. Genotyping was performed in 500 MI patients and 500 controls from the genetically isolated Newfoundland population to determine the prevalence of these gene variants and association with MI. Gene-gene interactions were also analyzed. The prevalence of combined carriers of FXIII-A V34L and FIIG20210A alleles was 12-fold higher in MI patients compared with controls (P = 0.002) and with 92% penetrance. There was disequilibrium of FXIII-A V34L allele to MI patients carrying FIIG20210A as a genetic background.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".