Integration of acoustical information in the perception of impacted sound sources: The role of information accuracy and exploitability.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sound sources are perceived by integrating information from multiple acoustical features. The factors influencing the integration of information are largely unknown. We measured how the perceptual weighting of different features varies with the accuracy of information and with a listener's ability to exploit it. Participants judged the hardness of two objects whose interaction generates an impact sound: a hammer and a sounding object. In a first discrimination experiment, trained listeners focused on the most accurate information, although with greater difficulty when perceiving the hammer. We inferred a limited exploitability for the most accurate hammer-hardness information. In a second rating experiment, listeners focused on the most accurate information only when estimating sounding-object hardness. In a third rating experiment, we synthesized sounds by independently manipulating source properties that covaried in Experiments 1 and 2: sounding-object hardness and impact properties. Sounding-object hardness perception relied on the most accurate acoustical information, whereas impact-properties influenced more strongly hammer hardness perception. Overall, perceptual weight increased with the accuracy of acoustical information, although information that was not easily exploited was perceptually secondary, even if accurate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it