Sleep-inducing pharmaceuticals: a comparison of melatonin, zaleplon, zopiclone, and temazepam.
Bibliographic record
Abstract
INTRODUCTION: Current military operations often require pharmaceutical methods to sustain alertness and facilitate sleep in order to maintain operational readiness. This study was designed to compare the sleep-inducing power of four medications. METHOD: There were 9 men and 14 women, ages 21-53 yr, who were assessed for psychomotor performance before and for 7 h after ingestion of a single dose of placebo, zaleplon 10 mg, zopiclone 7.5 mg, temazepam 15 mg, or time-released melatonin 6 mg. The experimental design was a double-blind crossover with counterbalanced treatment order. Subjects wore polysomnographic electrodes to record total sleep and sleep latency during 4-min periods with eyes closed immediately before and after each psychomotor test sequence. Subjective drowsiness was assessed by questionnaire. RESULTS: There were drug x trials interactions for zaleplon, zopiclone, and temazepam for total sleep, sleep latency, and subjective drowsiness. More sleep, shorter sleep latency, and more drowsiness occurred immediately after psychomotor testing compared to before testing for all medications. Melatonin did not cause any sleep prior to psychomotor testing sessions, but caused sleep and reduced sleep latency after psychomotor test sessions from 1 3/4 h to 4 3/4 h post-ingestion. CONCLUSIONS: The sleep-inducing power of the medications before psychomotor testing was zopiclone > zaleplon > melatonin > temazepam. The corresponding effect after psychomotor testing was zopiclone > melatonin > zaleplon > temazepam.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".