Discrimination of Brief Gaps Marked by Two Stimuli: Effects of Sound Length, Repetition, and Rhythmic Grouping
Bibliographic record
Abstract
We examined the effects of sound marker length, marker repetition, and rhythmic grouping on auditory gap discrimination. The discrimination ofthe duration of a gap between two markers was impaired by lengthening these markers (from 150 to 262.5 ms). Discrimination was impaired by lengthening the preceding marker relative to lengthening the following marker, while the impairment was not increased when both markers were lengthened compared with when only the preceding marker was lengthened. This indicates that the level of discrimination is not decided by a simple summation of the effects of the preceding and of the following marker's length. Moreover, discrimination of a gap between a short (S) and a long (L) marker and of a gap between a long and a short marker was improved by repeating the presentation of these gaps (ie by repeating the markers alternately as SLSLSL...): both types of discrimination led to near identical performance. Finally, under the repetition condition each type of discrimination was not related to the tendency for each individual to perceive the stimulus sequences as segmented into rhythmic chunks of a short tone followed by a long tone (as [SL][SL][SL]...), or those of a long tone followed by a short tone (as S][LS][LS][L...).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".