Discrimination of Brief Empty Time Intervals when the First Marker Is Tactile
Bibliographic record
Abstract
Abstract The present study investigated the discrimination of brief empty time intervals and compared three different sensory modality conditions for marking time: when two successive signals are tactile (intramodal condition, TT), and when a first tactile signal is followed by a either a visual (V) or an auditory (A) signal (intermodal conditions: TV and TA). Twelve participants completed a bisection task over the course of eight experimental sessions. Three factors were manipulated: the marker modality (TT, TV, and TA), the duration range (300 and 900 ms), and the preparation (certainty, uncertainty). In the latter case, participants knew that the first marker was T, but were uncertain about the modality of the second marker. In general, TT intervals were better discriminated than intermodal intervals at 300 ms, but this effect fades at 900 ms. No difference in the discrimination level was observed between the intermodal conditions. For the perceived duration, there was no difference between TT and TA conditions, but the TV intervals were perceived as longer than the TT intervals. As well, the TV intervals were perceived as longer than the TA intervals. These results are interpreted in terms of attentional and sensory effects caused by the signals themselves (onset and alerting properties, prior entry).
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".