Self-timing in Memory and Visual Search Tasks
Bibliographic record
Abstract
We investigated the ability of people to time themselves as they perform cognitive tasks. One \ngroup did a memory search task, another did a visual search task. After each response, \nparticipants estimated the duration of their own reaction time. In both tasks, correlations \nbetween reaction times and temporal judgments were significant, showing that people can \nprovide precise quantitative estimates of mental processes when they perform memory and visual \nsearch tasks. Increasing load lengthened reaction times and temporal estimates in both tasks. \nAccuracy of temporal judgments increased across blocks of experimental trials, showing \nconsiderable improvement in self-timing with practice although in visual search, improvement \nwas more pronounced under low load conditions. Results demonstrate excellent ability for selftiming \nof memory and visual search, but suggest that in visual search, self-timing is influenced by \nstimulus conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".