A review of caffeine’s effects on cognitive, physical and occupational performance
Bibliographic record
Abstract
Caffeine is consumed by over 80% of U.S. adults. This review examines the effects caffeine has on cognitive and physical function, since most real-world activities require complex decision making, motor processing and movement. Caffeine exerts its effects by blocking adenosine receptors. Following low (∼40 mg or ∼0.5 mg kg −1 ) to moderate (∼300 mg or 4 mg kg −1 ) caffeine doses, alertness, vigilance, attention, reaction time and attention improve, but less consistent effects are observed on memory and higher-order executive function, such as judgment and decision making. Effects on physical performance on a vast array of physical performance metrics such as time-to-exhaustion, time-trial, muscle strength and endurance, and high-intensity sprints typical of team sports are evident following doses that exceed about 200 mg (∼3 mg kg −1 ). Many occupations, including military, first responders, transport workers and factory shift workers, require optimal physical and cognitive function to ensure success, workplace safety and productivity. In these circumstances, that may include restricted sleep, repeated administration of caffeine is an effective strategy to maintain physical and cognitive capabilities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".