Using ISO3382 measures to evaluate acoustical conditions in concert halls
Bibliographic record
Abstract
Application of the ISO3382 standard can lead to the acquisition of large amounts of data describing conditions in a hall. The data could include the values of a number of measures at 6 or more octave band frequencies and for many combinations of source and receiver location. This paper discusses and gives examples of using this data to find important acoustical features. The amount of data can be reduced by calculating average values over the entire data set or for each sub-area of the hall. Various important spatial variations of acoustical conditions can often be better understood from plots of values versus source-receiver distance. The analysis approach will depend on the purpose of the study, which could be for comparisons with various criteria, for investigations of problems, or to better understand the acoustical properties of the hall. The significance of new measurements can be determined by comparing values: with proposed ideal criteria, with values in well-known halls, or with theoretical predictions. The significance of differences between two values should be considered in terms of published just noticeable differences for particular measures. Separately examining early and late sound levels can be a useful diagnostic tool for better understanding the acoustical properties of halls.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".