Stimuli and Normative Data for Detection of Ling-6 Sounds in Hearing Level
Bibliographic record
Abstract
PURPOSE: The purpose of this work was to develop and evaluate a calibrated version of the Ling-6 sounds for evaluation of aided detection thresholds. Stimuli were recorded, and data from calibration values in dB HL were developed. Aided performance was characterized in adults and children. METHOD: Stimuli were recorded, prepared, and transferred to a CD for testing. Initial testing was completed on 29 normally hearing young adults to determine typical responses in dB SPL and reliability. Corrections to dB HL were determined for each stimulus. Twenty-seven adults and 5 children with hearing losses were tested. RESULTS: Average normal sound field thresholds were 1 dB HL. Aided thresholds for adults varied with unaided hearing level and were better for low-frequency sounds. Adults and children performed differently, possibly because of greater hearing aid gain for children. CONCLUSIONS: Stimulus preparation and shaping resulted in a recorded, calibrated set of Ling-6 stimuli that provide flat normal thresholds in hearing level for normally hearing listeners. Typical performance ranges may vary with hearing level and prescription. More data are required to fully characterize this trend in the pediatric population.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".