Bibliographic record
Abstract
It is well-established that the smallest discrimination thresholds for interaural time differences (ITDs) are near 10 μs for normal hearing listeners. However, little is known about the hearing and training status of the test subjects from past studies. Previous studies also did not explicitly focus on the identification of the optimal stimulus and measurement technique to obtain the smallest threshold ITDs. Therefore, the first goal of the current study was to identify the stimulus and experimental method that maximizes ITD sensitivity. The second goal was to provide a precise threshold ITD reference value for both well-trained and un-trained normal hearing listeners using the optimal stimulus and method. The stimulus that yielded the lowest threshold ITD was Gaussian noise, band-pass filtered from 20 to 1400 Hz, presented at 70 dB sound pressure level. The best method was a two-interval procedure with an interstimulus interval of 50 ms. The average threshold ITD for this condition at the 75% correct level was 6.9 μs for nine trained listeners and 18.1 μs for 52 un-trained listeners.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".