Population-based cohort development in Alberta, Canada: a feasibility study.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In a climate of increasing privacy concerns, the feasibility of establishing new cohorts to examine chronic disease etiology has been debated. Our primary aim was to ascertain the feasibility of enrolling a geographically dispersed, population-based cohort in Alberta. We also examined whether enrolees would grant access to provincial health care utilization data and consider providing blood for future analysis. Using random digit dialling, 22,652 men and women aged 35 to 69 years, without diagnosed cancer, were recruited. Of these, 52.4 percent (N=11,865) enrolled; 84 percent of Alberta communities were represented. Approximately 97 percent of enrolees consented to linkage with health care data, and 91 percent indicated willingness to consider future blood sampling. Comparisons between the cohort and the Canadian Community Health Survey (Cycle 1.1) for Alberta demonstrated similarities in marital status and income. However, the cohort had a smaller proportion who had not finished high school, a greater proportion of nonsmokers and a higher prevalence of obesity. These findings indicate that establishment of a geographically dispersed cohort is feasible in the Canadian context, and that data linkage and biomarker studies may be viable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it