Buccal visible light spectroscopy and laser Doppler flowmetry: reliability analysis
Bibliographic record
Abstract
There are insatiable demands for new technologies to advance basic biological investigation at the microcirculatory level. Oxygen to see (O 2 C) is a newly developed system that combines laser Doppler flow (LDF) and visible light spectroscopy (VLS) technology. The aim of our study was to assess the reliability of O 2 C measurements applied to the buccal mucosa and to the thenar eminence in healthy volunteers. Microcirculatory hemoglobin oxygen saturation (μHbO 2 , %) and blood flow (flow, AU) were measured using an O 2 C (Lea Medizintechnik GmbH, Giessen, Germany) probe applied to the buccal mucosa and to the thenar eminence. Measurements were obtained simultaneously at two depths, superficial (2 mm) and deep (6 mm), every 2 seconds for 5 minutes and were recorded for later analysis. The procedure was repeated on another occasion at least 1 week apart. We studied 20 healthy subjects; 10 males and 10 females (mean age = 38 ± 18 years, range 21–74 years). Both μHbO 2 and flow measurements were consistently higher when measured from the deep tissue layers (6 mm) than those measured from the superficial layers, regardless of the site of measurement. Buccal mucosal μHbO 2 ranged from 78% to 96% and varied only minimally (CV: 4–7.5%), whereas there was a marked variability in flow measurements (CV: 29–63.9%). The reproducibility of buccal mucosal μHbO 2 and flow measurements were moderate to good (that is, intra-individual reliability, ICC: range 0.7–0.87, P < 0.05). However, only measurements from the superficial mucosal layers showed a moderate to good degree of inter-individual agreement (that is, inter-individual reliability, ICC: range 0.68–85, P < 0.001). LDF and VLS values measured on the thenar eminence were highly variable, were not reproducible, and the inter-individual agreement was poor. O 2 C provides reliable measurement of buccal μHbO 2 and microvascular flow. Skin measurements on the thenar eminence are highly variable and unreliable.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".