Normal incidence reflection measurements (TREX13): Inferences for lateral heterogeneity over a range of scales
Bibliographic record
Abstract
Normal incidence seabed reflection data suffer from a variety of ambiguities that make quantitative interpretation difficult. The reflection coefficient has an inseparable ambiguity between bulk density and compressional sound speed. Even more serious, reflection data are a function of other sediment characteristics including interface roughness, volume heterogeneities, and local bathymetry. Seafloor interface curvature is especially important and can lead to focusing/defocusing of the reflected field. An attempt is made with ancillary data including bathymetry, 400 kHz backscatter, and wide angle seabed reflection data to separate some of the mechanisms. Resulting analysis of 1–12 kHz reflection data suggest: (1) strong lateral sediment heterogeneity exists on scales of 10–100 m; (2) there are distinct geoacoustic regimes on the lee and stoss side of the ridge crest, and also between crest and the swale, and (3) the ridge crest geoacoustic properties are similar across distances of 6 km along two perpendicular transects (1 correlation). [Research supported by ONR Ocean Acoustics.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".