Bibliographic record
Abstract
The concept of bottom loss has traditionally been used as a measure of acoustic reflectivity and transmission at the ocean bottom. The measure was generally derived experimentally from measurements of transmission loss versus range, using a simple model that assumed perfect reflection at the sea floor to process the transmission loss data of bottom reflected signal paths. More recently, the interaction of sound with the ocean bottom has been described in terms of a geoacoustic model that defines a physical structure of sound speed, density and attenuation in the material beneath the sea floor. The model parameters are inferred from acoustic field data or observables derived from the field using sophisticated inversion techniques. The estimated model can be compared with bottom loss measurements through calculations of the plane wave reflection coefficient. This paper illustrates comparisons of bottom loss measurements for low- and high-frequency bands (50 –20,000 Hz) and calculations from estimated geoacoustic profiles for deep and shallow water environments. Conditions are discussed that limit the performance of present day inversion techniques: rough interfaces on and below the sea floor, consolidated material that supports shear wave propagation and range variation of sub-bottom structure. [Work supported by ONR Ocean Acoustics Team.]
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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 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".