Bibliographic record
Abstract
It has long been established that correlation-based measurement techniques, using, e.g., maximum length sequences and swept sines, outperform classical methods based on random Gaussian noise. Among the advantages of these modern techniques are better rejection of background noise and reduced measurement duration to achieve similar or better precision. These advantages are especially interesting in room and building acoustics, where many measurement positions typically have to be covered and background noise is often an issue, especially when measuring sound transmission loss or velocity level differences. Unfortunately, there is currently no provision in the ASTM standards on room and building acoustics that would allow the use of these modern measurement methods. To demonstrate the advantages of these methods, this contribution will present an example of measurements of the apparent sound transmission loss, i.e., measurements of sound pressure level differences and reverberation times. In addition to the standardized measurements according to ASTM E336, all measurements were repeated with maximum length sequences and swept sines. The results will be compared and the advantages of the modern techniques will be highlighted.
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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 | 0.000 | 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 | 0.001 |
| 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".