Bibliographic record
Abstract
OBJECTIVE: To compare blood pressure measurements taken in routine clinical practice using an automated recorder, the BpTRU (VSM MedTech Ltd, Coquitlam, Canada), with readings taken by a conventional mercury sphygmomanometer. METHODS: Fifty consecutive patients [28 women, 22 men; mean (+/-SD) age 62+/-16 years] referred to a specialist for management of hypertension had blood pressure taken on the first visit in random order using both a mercury sphygmomanometer and an automated device. RESULTS: The mean initial automated reading (mmHg) taken with the observer present (162+/-27/85+/-12) was similar to the mean manual blood pressure taken in duplicate (163+/-23/86+12). Both values were higher (P<0.001) than the mean of the next five readings taken with the automated recorder when the patient was resting quietly alone (142+/-21/80+/-12). Women exhibited a greater fall in blood pressure with the automated device than men. CONCLUSIONS: Use of an automated blood pressure recorder can eliminate some of the white-coat effect associated with readings taken by a mercury sphygmomanometer.
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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".