Seated inversion adversely affects vigilance tasks and suppresses heart rate and blood pressure
Bibliographic record
Abstract
Background: Inverted positions may arise with emergencies, work or recreational activities. Vigilance which can involve cognition, attention, and decision making is required for activities of daily living, in addition to the avoidance and escape from life threatening situations. Objective: The purpose of this study was to evaluate the effects of an inverted posture on vigilance, heart rate and blood pressure. Methods: Heart rate (HR) and blood pressure (BP), vigilance tasks (Tower of London (ToL), Selective Attention and Response Competition (SARC), Attention Networks Test (ANT)), anxiety and reaction time were assessed with 8 male subjects in an initial seated upright position, followed an inverted posture and returning to an upright position. Results: TOL was 63.4% and 40.7% slower and SARC was 10.4% and 11.7% slower during the inverted condition compared to the pre- and post-inversion upright assessments (p<0.01). There were no significant changes in ANT. Systolic BP (p<0.0001), diastolic BP (p=0.03), and HR (p<0.01) decreased during inversion, whereas anxiety scores increased 25% and 51% compared to pre- and post-inversion upright conditions. Conclusions: Under inverted conditions, vigilance task capabilities and reaction time were significantly hampered. These decrements could substantially impact responses to emergency situations.
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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) | 0.003 | 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".