Bibliographic record
Abstract
The overall objective of the Canadian Collaborative Project on the Genetic Susceptibility to Multiple Sclerosis (CCPGSMS) is to elucidate the pathogenesis of Multiple Sclerosis (MS). The aims of this thesis, as part of the CCPGSMS, were to 1) confirm the involvement of genetics in the susceptibility to MS 2) to examine the effects of the shared familial environment on MS risk and 3) to determine if a maternal effect can increase the risk to MS. Fourteen thousand nine hundred and ninety active Multiple Sclerosis (MS) clinic patients were screened as part of the CCPGSMS between the dates of Sept., 1994 and May,1996. From this group, 203 twin pairs, (80 monozygotic and 123 dizygotic), were identified. The proband-wise monozygotic twin concordance rate was 28.25% (SE. 5.84%) and the dizygotic twin concordance rate was 5.61% (S.E. 2.45%). The risk to the non-twin sibs of an index case was estimated at 2.49% (S.E. 0.74%) which was not significantly different than the dizygotic twin risk estimate, 0.05<p<0.10. This confirms the results of previous studies, and supports a strong genetic contribution to MS susceptibility. Five hundred and forty-five MS patients were identified with adoptive parents, and/or adopted sibs, and/or adopted children. The total adoptive first degree relatives of MS patients was 1185. Only one of these individuals had clinically definite MS. This was significantly different than the 25.2 affected individuals expected if the shared familial environment was important to the familial aggregation of MS, p=2.98 X 10"10. This supports the hypothesis that familial aggregation of M S is due primarily to genetics and not to the sharing of the familial environment. Nine hundred and thirty-six index cases were identified that had at least one half-sibling. There was no significant difference in the risk estimate between maternal half-siblings, 1.47% (S.E. 0.42%) and paternal half-siblings, 1.31% (S.E. 0.46%), 0.75<p<0.90. This argues against the contribution of a significant maternal effect to M S risk.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".