Auditory Noise Can Facilitate Body's Peripheral Temperature Switchovers
Bibliographic record
Abstract
Home is the context of an ambient-intelligence environment. Nonetheless, one can downsize the environment. For example, the human body as an environment, and by reading all possible bio-signals, this article can create control loops where many of these bio-signals can be used as sensory inputs to make humans aware of their current perceptual-cognitive state. In this article, the authors present an example where the peripheral temperature is used as a marker to know when a human switchover from a stress state to a calm state happens. The switchovers are controlled by the sympathetic and parasympathetic nervous system. The authors showed that finger temperature can be modulated by an effective auditory noise, and in four of the six tested subjects, 70 dBSPL was the optimal noise. These results open the possibility of making personalized, adaptive and anticipatory devices capable of modulating the switchover from a stress state to a calm state.
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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".