© 2013 Canadian Medical Association or its licensors CMAJ OPEN E37 Research CMAJ OPEN Results from the Canadian Health Measures Survey
Bibliographic record
Abstract
indicate that 19 % of Canadians (4.6 million people) have hypertension. Worldwide, over 54 % of stroke, 47 % of ischemic heart disease and 13.5 % of all deaths are because of high blood pressure.2–4 Blood pressure measure-ment is one of the most commonly performed tests in family practice. However, because of the inherent variability5 of blood pressure, issues about where, by whom and how it is measured are of paramount importance. Accuracy can be affected by factors such as equipment, patient or operator variability, white-coat hypertension, masked hypertension, night-time dippers (hypertensive patients who display noctur-nal decreases in blood pressure) versus nondippers and inter-visit variability and episodic peaks. The importance of the accurate measurement of blood pressure is underscored by the fact that reductions in systolic blood pressure of more than 5 mm Hg, or even as small as 2–4 mm Hg, are clinically impor-tant.6 The average effect on blood pressure of a single antihy-pertensive drug at a standard dose or a single lifestyle change can be as high as 10 mm Hg systolic and 6 mm Hg diastolic.7,8 The end result is that the measurement error frequently exceeds the effect size of therapy or lifestyle modification. Because community pharmacies are frequently visited by patients and because pharmacists are encouraged to monitor Comparison of blood pressure measurements using an automated blood pressure device in community pharmacies and family physicians ’ offices: a randomized controlled trial
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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.509 | 0.185 |
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".