Interval discrimination across different duration ranges with a look at spatial compatibility and context effects
Bibliographic record
Abstract
In the present study, a time discrimination task was used to investigate the effect of different contexts for intervals varying from 400 to 1600 ms. A potential time-space interaction was controlled, and participants used both manual responses (Experiments 1 and 2) and vocal responses (Experiment 3). Three ranges of durations were employed (short, middle and long), and within each range condition, three standard values were used (400, 700, and 1000 ms; 700, 1000, and 1300 ms; and 1000, 1300, and 1600 ms). Within each range, standard intervals were randomized (Experiments 1 and 3) or remained constant (Experiment 2) within a block of trials. Our results suggest that context influences time discrimination performances only when the temporal range under investigation is below 1300 ms and the temporal intervals varied within blocks. In the case of temporal intervals longer than 1300 ms, participants presented a tendency to respond "long" independently of the procedure used. Moreover, our results suggested that performances in a discrimination task are mainly influenced by the fact of varying standard durations within blocks, and not much by the time-space compatibility.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".