Realism assessment of sonic boom simulators
Bibliographic record
Abstract
Developments in small supersonic aircraft design are predicted to result in low-intensity sonic booms. Booms generated by current aircraft are similar to those that led to the ban on commercial supersonic fli ght over the US, so are unsuitable for parametric studies of psychoac oustic response to low-intensity booms. Therefore, simulators have be en used to study the impact of predicted low-intensity sonic booms. H owever, simulators have been criticized because, when simulating conv entional-level booms, the sounds were observed to be unrealistic by p eople experienced in listening to sonic booms. Thus, two studies were conducted to measure the perceived realism of three sonic boom simul ators. Experienced listeners rated the realism of conventional sonic boom signatures when played in these simulators. The effects on percei ved realism of factors such as duration of post-boom noise, exclusion of very low frequency components, inclusion of ground reflections, a nd type of simulator were examined. Duration of post-boom noise was f ound to have a strong effect on perceived realism, while type of simu lator had a weak effect. It was determined that post-boom noise had t o be at least 1.5 seconds long for the sound to be rated very realist ic. Loudness level did not affect realism for the range of sounds pla yed in the tests (80-93 dB ASEL).
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".