Additional file 1 of Normal sex and age-specific parameters in a multi-ethnic population: a cardiovascular magnetic resonance study of the Canadian Alliance for Healthy Hearts and Minds cohort
Bibliographic record
Abstract
Additional file 1: Figure S1. Flow chartfor patient selection. RI, magnetic resonance imaging; LVEF, leftventricular ejection fraction; LV mass, left ventricular mass; CVD,cardiovascular disease; PURE, prospective urban and rural epidemiologicalstudy; CPTP, the Canadian Partnership for Tomorrow Project; BC Generations,British Columbia; OHS, Ontario Health Study; Atlantic PATH, AtlanticPartnership for Tomorrow's Health; MHI, Montreal Heart Institute. Figure S2. Age-specific trends for males and females for A) LV end-systolic volumesindexed to BSA (ml/m2); B) LV end-diastolic volumes indexed to BSA(ml/m2); and C) LVEF (%). Linear regression was applied to model the data,which are presented as mean (blue lines) and 95% confidence intervals (redlines). Figure S3. Representativeexamples of Bland Altman plots for inter-observer variability of absolute leftand right ventricular stroke volumes (ml). Figure S4. Representativeexamples of Bland Altman plots for intra-observer variability of absolute leftand right ventricular stroke volumes (ml).
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.
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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.698 | 0.068 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".