Estimation of Modified Concordance Ratio in Sib-Pairs: Effect of Consanguinity on the Risk of Congenital Heart Diseases
Bibliographic record
Abstract
Family studies are widely used for research into genetic and environmental influences on human traits. In this paper, we establish statistical methodology for the estimation of a new measure of sib similarity with respect to dichotomous traits measured on each member of within family sib-pair. We call this parameter "excess risk." For inference problems involving a single sample, we construct a large sample confidence interval on the concerned parameter. It has long been suspected that consanguinity is a risk factor for many genetic defects. Therefore, we establish a procedure to test the significance of the difference between excess risk parameters in a sample of consanguineous marriages and another sample of non-consanguineous marriages. We apply the methodology to data from a hospital-based congenital heart defects registry in Saudi Arabia, a population in which consanguinity is quite common.
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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 | 0.001 | 0.005 |
| 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) | 0.000 | 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".