67 A Population-Based Delivery-Based Longitudinal Maternal-Child Health Database
Bibliographic record
Abstract
The overall goal of this project was to establish a Maternal-Child Health Database to be used to provide important population data needed for epidemiologic research ultimately aimed at improving health care outcomes. The specific objectives were: 1) To develop the means for linking data from various health, administration, educational and social assistance databases and 2) To develop the procedures needed to maintain strict confidentiality and privacy of individuals in the database. A database of all mothers and infants delivered while resident in Nova Scotia (Atlee Perinatal Database) provided the population-based characteristics. By linking databases with information on subsequent health events and social assistance benefits as well as education events, the perinatal database becomes longitudinal in terms of the epidemiologic questions that can be addressed. The problem of maintaining confidentiality and privacy of individuals was resolved by establishing a file of unique encrypted links, or cross-walk file, for each pair of databases. Linking of data specifically related to the project of interest can then be carried out on a project-by-project basis by using the pre-determined cross-walk file without reference to specific individual identifiers in each of the databases involved. What is produced is an analysis file containing no individual identifiers except for unique project-specific individual study numbers with no relationship to the original database identifiers. These procedures are carried out under the scrutiny of a Joint Data Access Committee, a technical advisory committee to Research Ethics Boards. This committee consists of custodians of the commonly-used databases, epidemiologists, clinical investigators and an expert in health law and ensures that the confidentiality and privacy of individuals in the databases are maintained. These procedures are consistent with the recently released Canadian Institutes of Health Research Guidelines on Secondary Use of Personal Information in Health Research, November 2002. Using these procedures, the following databases have been linked: Atlee Perinatal Database and the Hospital Admissions (CIHI), Physicians' Office Visits (MSI), Vital Statistics, Perinatal Follow-Up, Maternal Serum Screening, Fetal Anomaly, Pediatric Cardiology, Childhood Epilepsy, Family Benefits and Cancer Registry Databases. Five studies are currently underway using the Maternal-Child Health Database. The ability to link longer term outcomes following perinatal events augments studies of perinatal and childhood health
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.010 |
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".