Bibliographic record
Abstract
Mental fatigue is a psychobiological state induced by sustaining cognitive attention on one, or multiple, tasks (van der Linden et al., 2003). Mental fatigue has a negative effect on both cognitive and physical performance (Marcora, 2009). The quantifiable effect of mental fatigue on behaviour, performance, and mood is also still under investigation, and as of yet there is no gold standard for inducing the state and measuring it. The purpose of this investigation was to ascertain the effect of the AX-CPT cognitive task, and a common neutral control condition on mental fatigue. Forty-two participants (mean age = 21; males = 16,) were assigned either the experimental (AX-CPT) condition, or the control (neutral documentary) condition, each lasting 90 minutes. Mental fatigue was measured via the Brunel Mood Scale pre and post-test. Participants also completed a wall sit to voluntary exhaustion post-test. Results indicated a significant interaction of time and group (F(1, 40) = 14.965, p = 0.05), with participants in the experimental group reporting significantly higher levels of post-test mental fatigue (M = 11.71, SD = 3.6) than the control group (M = 5.81, SD = 3.61). A significant difference in wall sit times was also reported, with the experimental group performing significantly worse (M = 123.33, SD = 42.85) than the control group (M =171.05, SD = 90.51). Conclusions include that the AX-CPT is a valid method for inducing mental fatigue, however some concerns regarding the control condition arose. Many participants in the control group expressed elevated levels anger and tension, indicating that it may not be the best approach for the population.
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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 | 0.002 |
| 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 | 0.001 |
| 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".