Influence of long-term fasting and intermittent fasting on the cognitive abilities
Bibliographic record
Abstract
Fasting as skipping or abstaining from eating or drinking for a certain time is known mainly due to religion. In addition to religious reasons, we can also fast for weight loss or detoxication. We have decided to examine the impact of fasting on the human organism more closely, especially on the cognitive functions, such as short-term memory, attention, concentration, language skills, abstract reasoning, etc. The research completed 16 participants (M+F; 25.8y±2.7; 179.5cm±11.6; 74.6kg±15.1). There were divided into 2 groups (long-term fasting (LTF) and intermittent fasting (IF)). For measurement cognitive function we used Montreal Cognitive Assessment (MoCA), which was completed by all participants in the study before and after the fasting period. The research completed 16 participants. The total score of MoCA decreased in both group after the fasting period, more in the IF group (-1.1 points), but not statistically significant. Values for short-term memory evaluation decreased in both groups, also in the IF group more (-0.9 points), there was a large effect size. Verbal production values decreased in both group and these changes were statistically significant with small effect size. Our results suggest that long-term fasting and intermittent fasting may reduce genitive abilities. Especially short-term memory can be influenced by intermittent fasting. Both fasting methods decreased the level of verbal production.
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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 | 0.001 |
| 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".