Age-related changes in within- and between-channel gap detection using sinusoidal stimuli
Bibliographic record
Abstract
Pure tone gap stimuli with identical (within-channel) or dissimilar (between-channel) marker frequencies of 1 and 2 kHz were presented to young and old listeners in a two-interval forced choice gap detection task. To estimate the influence of extraneous duration cues on gap detection, thresholds in the between-channel conditions were obtained for two different sets of reference stimuli: reference stimuli that were matched to the overall duration of the gap stimulus, i.e., two markers plus the gap, and reference stimuli that were fixed at the combined duration of the two markers excluding the gap. Results from within-channel conditions were consistent with previous studies, i.e., there were small but highly reliable age differences, smaller gap thresholds at longer marker durations, and an interaction between the two variables. In between-channel conditions, however, age differences were not as clear cut. Rather, the effect of age varied as a function of duration cue and was more pronounced when stimuli were matched for overall duration than when the duration of the reference tone was fixed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".