Muscle VO <sub>2</sub> and forearm blood flow repeatability during venous and arterial occlusions in healthy and coronary heart disease subjects
Bibliographic record
Abstract
This study aims were: 1) to assess forearm blood flow (FBF) and muscle oxygen consumption (mVO2) repeatability assessed with near-infra red spectroscopy (NIRS) during venous occlusions (VO) in middle aged healthy subjects and patients with stable coronary heart disease (CHD), 2) to assess the agreement between mVO2 calculated from NIRS signals during VO and arterial occlusion (AO) in 18 middle aged healthy subjects and 12 patients with CHD. FBF and mVO2 were measured using NIRS during 2 successive VO (1-min duration), followed by a 5-min AO. Repeatability for FBF and mVO2 during VO was assessed with intra class correlation (ICC), coefficient of variation (CV %) and agreement between VO and AO mVO2 was assessed with a Bland and Altman analysis. FBF and mVO2 during VO were highly reproducible in healthy (FBF: ICC 0.73, CV% 9.75; mVO2: ICC 0.89, CV% 12.6) and CHD subjects (FBF: ICC 0.95, CV% 10.26; mVO2: ICC 0.98, CV% 7.92). VO and AO mVO2 were in agreement in healthy (mean bias: 0.002 mL O2.min-1.100g-1) and CHD subjects (mean bias: 0.014 mL O2.min-1.100g-1). FBF and mVO2 measured with NIRS during VO and/or AO are highly reproducible methods to assess microvascular function in healthy subjects and stable CHD patients.
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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 | 0.002 |
| 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 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".