Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populations in Quebec and Switzerland
Bibliographic record
Abstract
At the Montreal site, 195 participants have consented to participate and their blood was drawn. We have another 15 men that have agreed to participate and their blood will be drawn in the next few months. We have recruited a total of 42 controls. The pedigrees for all controls and cases have been drawn. Ishihara charts were shown to all cases and controls and the results were recorded. At the Switzerland site, case ascertainment is underway. To date, an additional three urologist and a radio-oncologist have given their support to this project. 319 patients have been contacted and 102 have had a consultation with a DNA sampling. An additional 28 men have given their consent to participate at the Sion site. As well as continuing to look at the X chromosome for relevant markers, we have genotyped 11 microsatellite markers, spanning 34 megabases on chromosome 7, in approximately 140 of our cases. We observed suggestive differences between cases and controls for two markers located approximately 2.75 megabases apart at 7q11.23 (D7S2518 and D7S2204) . We also conducted the first phase of a SNP discovery project. We resequenced CHEK2 in 75 Ashkenazi Jewish individuals (25 prostate cancer, 25 breast cancer and 25 controls). We identified 5 novel SNPs. These are now under detailed investigation. Finally, we completed and published our study of the putative prostate cancer gene, MSR1.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".