Target echo and clutter calculations, including time spreading using normal-mode group velocities.
Bibliographic record
Abstract
The shallow-water normal-mode reverberation approach [D. D. Ellis, J. Acoust. Soc. Am. 97, 2804–2814 (1995)] can be extended to handle the echo from a target or discrete clutter objects. Normal modes are used to handle the propagation, and ray-mode analogies are used to handle the echo and scattering. The time spreading of the echo can be approximated using the modal group velocities. This description for the time spreading is approximate, but the computations are quite efficient, since the normal modes need only be calculated at one frequency. The target can be point-like and mode functions can be used, or the target can be considered more extended and the mode amplitude envelopes can be used. The formulation will be presented, along with a number of calculations based on problems from the ONR Reverberation Modeling Workshops. [Work supported in part by ONR, Code No. 321OA.]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".