Measures of Variations in Performance During a Sustained Attention Task
Bibliographic record
Abstract
In this study the authors developed and explored measures of short-term variations in accuracy on a test of sustained attention, a departure from traditional measures of average performance over long periods. The study participants were normal young adults, actively engaged in a continuous performance test (CPT). Both correct (hits) and incorrect (misses) responses to CPT targets appeared to aggregate in runs (2 or more consecutive hits or misses). Results of a Monte-Carlo procedure indicated that these runs were longer and fewer than would occur if hits and misses were randomly distributed. Average accuracy decreased between the first and second 5-min quarter of the test, then remained level. The length of hit runs followed the same pattern. However, other aspects of performance continued to change. The amount of time participants spent in miss runs began to increase significantly in the third quarter, and the frequency of miss runs did not increase until the fourth quarter. Explanations of these findings based upon changes in perceptual sensitivity or upon phasic increases in arousal caused by hits were rejected by further analysis. There was evidence that the length of miss runs was limited by a target-expectancy effect created by the specific parameters of our CPT. The authors conclude that measures of variations in performance reveal aspects of vigilance that are not tapped by traditional measures, and that factors that initiate, sustain and terminate both hit and miss runs are important targets of future research. Additional research is needed to determine whether or not the particular measures developed in this study may contribute to the understanding of attention problems in clinical populations.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".