Factors Affecting Consent Rate for Whole Genome Sequencing of Patients with Congenital Heart Disease
Bibliographic record
Abstract
The Whole Genome Sequencing Project initiated by The Hospital for Sick Children of Toronto intents to enroll patients between one to eighteen years of age with congenital heart disease to test the efficiency of such a method for potential personalized diagnoses and treatments. Twenty-five randomly approached patients were chosen to be observed of their consent rate to the project based on factors of age, gender, ethnicity, presence of heart diseases in the patient’s family, and type of congenital heart disease represented. Females and ethnicities not of European descent are considered to be a part of the minority groups, generally being under represented thus having a lower consent rate. There were no significant correlations between consent rates and familial history of heart disease, type of heart disease and age groups. All these findings can aid in future studies of the SickKids Hospital; which patients should be approached for higher consent rates, and the inclusivity of minority groups to alleviate bias in medical studies.
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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 | 0.022 | 0.134 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".