Variability in acoustic transmission loss over a rough water surface
Bibliographic record
Abstract
Variability in the acoustic transmission loss of impulsive sounds propagating in the atmosphere over a rough water surface was measured over time scales of 1–2 h at a fixed range of 250 m. On two separate days (26 and 30 May 2012), a propane cannon source was deployed on the upper deck of a ship. Once per minute, the propane cannon fired volleys of four shots that were recorded on a receiver deployed on a small boat tethered upwind of the ship. Meteorological conditions and sea state were comparable on both days, resulting in similar observations for transmission loss: mean and standard deviation of 64 ± 5 dB (26 May) and 66 dB ± 4 dB (30 May). The variability in transmission loss was high, with minimum and maximum values of 48 and 75 dB (26 May) and 53 and 77 dB (30 May). The transmission loss measured throughout the experiment exceeded the 48 dB predicted by assuming spherical spreading, since the receiver was upwind of the source. Measured results are compared to transmission loss computed from a parabolic equation model using an ensemble of turbulence and rough sea surfaces estimated from the meteorological conditions on board the ship.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".