Scalene and sternocleidomastoid activation during normoxic and hypoxic incremental inspiratory loading
Bibliographic record
Abstract
The purpose of this study was to examine scalene (SA) and sternocleidomastoid (SM) activation during normoxic (norm-ITL; FIO2 = 21%) and hypoxic (hyp-ITL; FIO2 = 15%) incremental inspiratory threshold loading (ITL). Thirteen healthy participants (33 ± 4 years, 9 female) performed two ITL tests breathing randomly assigned gas mixtures through an inspiratory loading device where the load was increased every two minutes until task failure. SA and SM root mean square (RMS) electromyography (EMG) were calculated and expressed as a percentage of maximum (RMS%max) to reflect muscle activation intensity. Myoelectric manifestations of fatigue were characterized as decreased SA or SM EMG median frequency during maximum inspiratory pressure maneuvers before and after ITL. Dyspnea was recorded at baseline and task failure. Ventilatory parameters and mouth pressure (Pm) were recorded throughout the ITL. SA,RMS%max and SM,RMS%max increased in association with ITL load (p ≤ .01 for both). SA,RMS%max was similar between norm-ITL and hyp-ITL (p = .17), whereas SM,RMS%max was greater during the latter (p = .001). Neither SA nor SM had a decrease in EMG median frequency after ITL (p = .75 and 0.69 respectively). Pm increased in association with ITL load (p < .001) and tended to be higher during hyp-ITL compared to norm-ITL (p = .05). Dyspnea was similar during both conditions (p > .05). There was a trend for higher tidal volumes during hyp-ITL compared to norm-ITL (p = .10). Minute ventilation was similar between both conditions (p = .23). RMS,%max of the SA and SM increased linearly with increasing ITL. The presence of hypoxia only increased SM activation. Neither SA nor SM presented myoelectric manifestations of fatigue during both conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".