Hearing thresholds under acute hypoxia and relationship to slowing in the auditory modality.
Bibliographic record
Abstract
BACKGROUND: Acute hypoxia slows reaction time to visual stimuli and it has been proposed that this slowing can be accounted for by a decrease in perceived brightness. Auditory slowing could be accounted for in an analogous manner if hypoxia decreases perceived loudness, as reflected by an increase in pure-tone thresholds. However, evidence concerning the effects of hypoxia on auditory thresholds is contradictory and we performed an experiment to clarify this issue. Pilot work suggested that thresholds were raised due to noise from our breathing apparatus used to deliver the low O2 mixtures and we eliminated this artifact by measuring thresholds while the subjects held their breath. METHODS: The six subjects breathed either air as a control through an oro-nasal mask or low O2 mixtures to maintain arterial blood oxygen saturation at 74% while thresholds between 500-4000 Hz were measured with an audiometer during breathholding. RESULTS: Hypoxia produced a statistically significant but practically insignificant decrease in thresholds of 1 dB across all frequencies tested. CONCLUSIONS: Our results are consistent with the view that audition is relatively insensitive to hypoxia and that the slowing observed with auditory stimuli cannot be accounted for by an increase in auditory thresholds. Some alternative hypotheses which could account for this slowing are proposed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".