Investigation of the validity of radiosity for sound-field prediction in cubic rooms
Bibliographic record
Abstract
This paper explores acoustical (or time-dependent) radiosity using predictions made in four cubic enclosures. The methods and algorithms used are those presented in a previous paper by the same authors [Nosal, Hodgson, and Ashdown, J. Acoust. Soc. Am. 116(2), 970-980 (2004)]. First, the algorithm, methods, and conditions for convergence are investigated by comparison of numerous predictions for the four cubic enclosures. Here, variables and parameters used in the predictions are varied to explore the effect of absorption distribution, the necessary conditions for convergence of the numerical solution to the analytical solution, form-factor prediction methods, and the computational requirements. The predictions are also used to investigate the effect of absorption distribution on sound fields in cubic enclosures with diffusely reflecting boundaries. Acoustical radiosity is then compared to predictions made in the four enclosures by a ray-tracing model that can account for diffuse reflection. Comparisons are made of echograms, room-acoustical parameters, and discretized echograms.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".