The Select Committee on the election act and reform of the voting system in Quebec
Bibliographic record
Abstract
DOC-2/DAB2 interactive protein (DAB2IP) is a novel identified tumor suppressor gene that inhibits cell growth and facilitates cell apoptosis. One genetic variant in DAB2IP gene was reported to be associated with an increased risk of aggressive prostate cancer recently. Since DAB2IP involves in the development of lung cancer and low expression of DAB2IP are observed in lung cancer, we hypothesized that the variations in DAB2IP gene can increase the genetic susceptibility to lung cancer. In a case-control study of 1056 lung cancer cases and 1056 sex and age frequency-matched cancer-free controls, we investigated the association between two common polymorphisms in DAB2IP gene (-1420T>G, rs7042542; 97906C>A, rs1571801) and the risk of lung cancer. We found that compared with the 97906CC genotypes, carriers of variant genotypes (97906AC+AA) had a significant increased risk of lung cancer (adjusted odds ratio [OR] = 1.33, 95%CI = 1.04-1.70, P = 0.023) and the number of variant (risk) allele worked in a dose-response manner (P(trend) = 0.0158). Further stratification analysis showed that the risk association was more pronounced in subjects aged less than 60 years old, males, non-smokers, non-drinkers, overweight groups and in those with family cancer history in first or second-degree relatives, and the 97906A interacted with overweight on lung cancer risk. We further found the number of risk alleles (97906A allele) were negatively correlated with early diagnosis age of lung cancer in male patients (P = 0.003). However, no significant association was observed on the -1420T>G polymorphism. Our data suggested that the 97906A variant genotypes are associated with the increased risk and early onset of lung cancer, particularly in males.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".