Caffeine effects on physical and cognitive performance during sustained operations.
Bibliographic record
Abstract
PURPOSE: This study examined caffeine (CAF) effects on physical performance and vigilance during 4 d and 3 nights of sustained operations in Special Forces personnel. METHODS: There were 20 soldiers (28.6 +/- 4.7 yr, 177.6 +/- 7.5 cm, 81.2 +/- 8.0 kg) who were divided equally into placebo (PLAC) and CAF groups. A 4-km run that included three obstacles (OBST) was completed each morning with the performance on Day 2 representing control (CON) after familiarization on Day 1 and an 8-h sleep. From 01:30 to 06:15 of Days 3-5, soldiers performed two 2-h vigilance (VIG) sessions in the field. PLAC or 200 mg of CAF was administered at 21:45 of Days 2-4 and at 01:00, 03:45, and approximately 07:00 on Days 3-5. The run commenced within 30 min of the final dose. Soldiers were provided a 4-h sleep period from 13:30-17:30 during Days 3 and 4. RESULTS: VIC during Days 3-5 was greater for CAF vs. PLAC and not different from CON. Total run time was faster for CAF (29.7 +/- 2.0 min) compared with PLAC (30.7 +/- 2.9 min) on Day 3 due to faster completion of OBST (8.7 +/- 0.7 min vs. 9.2 +/- 1.0 min for CAF and PLAC, respectively). Thereafter, run times decreased for both groups on Days 4 and 5 compared with CON due primarily to an increased pace between OBST. CONCLUSIONS: it was concluded that CAF maintained both vigilance and physical performance during sustained operations that require periods of overnight wakefulness and restricted opportunities for daytime 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".