Cardiorespiratory optimization during improvised singing and toning
Bibliographic record
Abstract
We evaluated the effect of different forms of singing on cardiorespiratory physiology, and we aimed at disentangling the role of breathing from that of vocal production. Cardiorespiratory recordings were obtained from 20 healthy adults at rest and during: a) singing of familiar slow songs as in the standard form of Western culture; b) improvised vocalization of free vowel sounds, known as toning. To disentangle the role of breathing from that of vocal production, we compared the vocal conditions with matched breathing-only conditions. Toning significantly improved heart rate variability, ventilatory efficiency and slowed respiration to almost exactly six breaths per minute (p < 0.001), a pattern that is known to optimize cardiovascular function and that coincides with the period of endogenous circulatory rhythms. Singing songs also positively impacted cardiorespiratory function, although to a lesser extent. The breathing pattern imposed upon participants in the absence of vocal production was sufficient to generate the physiological benefits. The effects of toning are similar to what has been previously described as a result of engaging in formal breathing exercises. Toning and singing may offer an engaging and cost effective tool to trigger beneficial respiratory patterns and the related cardiovascular benefits.
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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 | 0.001 |
| 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".