Additional file 1 of Online clinical pathway for chronic kidney disease management in primary care: a retrospective cohort study
Bibliographic record
Abstract
Additional file 1: Table S1. Characteristics of cohorts used for assessing the secondary outcomes of ACEi/ARB and Statin dispense (p 2-3). Table S2. Sensitivity analyses for the primary outcome: estimates of the pre-to-post change in slope for ACR measurements by zone (p 4). Table S3. Sensitivity analyses for ACEi/ARB use: estimates of the pre-post change in slope for ACEi/ARB use in a modified quarter, for the diabetes cohort and the cohort with severe albuminuria and no diabetes (p 5). Table S4. Sensitivity analyses for statin use: estimates of the pre-post change in slope for statin use in a modified calendar quarter, for the diabetes cohort and the no diabetes/older than 50 cohort (p 6). Figure S1. Alberta Health Services Zone Map (p 7). Figure S2. Adjusted proportion of patients in the Calgary zone with an ACR measurement in a 28-day period (p 8). Figure S3. Adjusted proportion of patients in the Edmonton zone with an ACR measurement in a 28 day period (p 9). Figure S4. Adjusted proportion of patients with diabetes who were dispensed an ACEi/ARB in a 28-day period by zone (p 10). Figure S5. Adjusted proportion of patients without diabetes but with severe albuminuria who were dispensed an ACEi/ARB in a 28-day period by zone (p 11). Figure S6. Adjusted proportion of patients with diabetes who were dispensed a statin in a 28-day period by zone (p 12). Figure S7. Adjusted proportion of patients without diabetes but over the age of 50 who were dispensed a statin in a 28-day period by zone (p 13).
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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 | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.566 | 0.051 |
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".