Between‐day reliability of local thermal hyperemia in the forearm and index finger using single‐point laser Doppler flowmetry
Bibliographic record
Abstract
Abstract Objective To assess between‐day reliability for LTH in glabrous and nonglabrous index finger skin and nonglabrous forearm skin, with single‐point laser Doppler flowmetry. Methods Part‐1: In healthy, habitually active males (n=10), LTH was examined twice (~7‐10 days apart) for both skin types on the index finger. Part‐2: Identical testing was performed on the volar forearm. Local heating (33‐42°C at 1°C·20 s−1 + 20 minutes at 44°C) was performed at all skin sites and baseline, initial peak, and plateau phases were identified. Data were expressed as raw CVC (laser‐Doppler flux/MAP), and as CVC normalized to baseline (%CVC33°C) and maximum heating (%CVC44°C). Reliability was assessed using between‐day mean difference, %CV, and ICC. Results Reliability (%CV) was poor at baseline for all forms of data presentation and for other phases with %CVC33°C. At the initial peak and plateau, reliability was moderate‐poor (20%‐26%) for CVC and good‐moderate (6%‐18%) for %CVC44°C. Reliability was good‐moderate for vasodilatory onset time (10%‐23%) and time to initial peak (6%‐13%). Conclusions For all sites, LTH reliability was acceptable for the timing, and for the initial peak and plateau using CVC or %CVC44°C.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".