Determination of sound-field diffusion indices based on FMBEM incidence directivity analysis
Bibliographic record
Abstract
Regarding the diffuseness of sound field, several indices and their measurement methods have been proposed in terms of isotropy of traveling waves. In this paper, we attempt to calculate two kinds of diffusion indices based on the incidence directivity analysis employing the fast multipole boundary element method (FMBEM). The directivity analysis is performed for steady-state sound fields in a rectangular room with changing the absorption condition of the walls. As for diffusion indices, the directional diffusion coefficient is determined from the deviation of directivity of sound intensity, while alternative isotropy indicator is calculated through the spherical expansion of the directivity. The numerical results show general tendencies that the former index is almost constant, whereas the latter index decreases with increasing the frequency. As a common tendency, it is confirmed that the indices become higher in a reflective room condition, and remarkable dips occur around the natural frequencies when absorbing walls are unevenly distributed. Moreover, concerning the receiving cell, the size of it has little effect on the indices. On the other hand, it is verified that the indices become higher with the receiving cell near the point source.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".