Trapezius muscle metabolism measured with NIRS in helicopter pilots flying a simulator.
Bibliographic record
Abstract
INTRODUCTION: This study examined metabolic and hemodynamic responses during night vision goggle (NVG) induced neck strain among military helicopter pilots. We hypothesized that near infrared spectroscopy (NIRS) would be capable of identifying metabolic differences in the trapezius muscles of pilots between simulated flights with and without NVG. METHODS: There were 33 pilots who were monitored on consecutive days during Day and NVG flight simulator missions. NIRS probes were attached bilaterally to the trapezius muscles at the C7 level to record total oxygenation index (TOI, %), total hemoglobin (tHb), oxyhemoglobin (HbO2), and deoxyhemoglobin (HHb). RESULTS: Significant differences in tHb were found between Day (0.51+/-2.31 micromol x cm (-1)) and NVG (4.14 +/- 2.74 micromol x cm(-1)) missions, and for HbO2 (Dayend 2.63+/-1.64 micromol x cm(-1); NVGend 5.77+/-1.98 micromol x cm(-1)). Significant left and right side differences between Day and NVG were found for tHb (NVGleit -1.83+/-2.55; NVGright 10.45+/-2.86 micromol x cm(-1)), HbO2 (NVGleft 1.77+/-1.90; NVGright 9.95+/-2.07 micromol x cm(-1)), and HHb (Dayleft -1.84+/-0.95; Dayright -2.32+/-0.87 micromol x cm (-1); NVGleft -3.60+/-1.05 micromol x cm(-1); NVGright 0.49+/-1.16 micromol x cm(-1). DISCUSSION: These results support NIRS's utility in assessing the significant metabolic and hemodynamic effects of NVG on neck musculature during real-time missions for 1) left and right side differences; and 2) Day vs. NVG missions. The additional mass of the NVG equipment does increase the metabolic stress of these muscles during simulated missions.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".