Influence on Human Sleep Patterns of Lowering and Delaying the Minimum Core Body Temperature by Slow Changes in the Thermal Environment
Bibliographic record
Abstract
STUDY OBJECTIVES: We hypothesized that appropriate changes in thermal environment would enhance the quality of sleep. DESIGN/SETTING: Controlled laboratory study. PARTICIPANTS: Healthy young men (n = 7, mean age 26 years). INTERVENTIONS: Nocturnal sleep structures in semi-nude subjects were compared between a condition where an ambient temperature (Ta) of 29.5 degree C was maintained throughout the night (constant Ta), and a second condition (dynamic Ta) where Ta changed slowly within the thermoneutral range (from 27.5 C to 29.5 degree C). MEASUREMENTS AND RESULTS: Statistically significant (P < 0.05) results included a lower and a later occurrence of minimum core body temperature (Tc), and a longer duration of slow-wave (stages 3+4) sleep in dynamic versus constant T. However, total sleep time, sleep efficiency, the total durations of light (stages 1+2) and rapid eye movement sleep, and the latencies to sleep onset, slow-wave sleep, and rapid eye movement sleep did not differ between conditions. CONCLUSIONS: Lowering the minimum and delaying the nadir of nocturnal Tc increases slow-wave sleep (probably by an increase of dry heat loss); use of this tactic might improve the overall quality of sleep.
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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) | 0.001 | 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".