Bibliographic record
Abstract
This report describes the objectives and some of the results from a three-year joint collaboration between DRDC Atlantic and the Applied Research Laboratory of the Pennsylvania State University to analyze and model reverberation data. Reverberation data up to 4 kHz had been collected on towed arrays during the initial (1996-2002) NATO MILOC Rapid Environmental Assessment exercises and more recent JRPs (Joint Research Projects) between the US, Canada, and SACLANTCEN (now NURC, NATO Undersea Research Centre). Preliminary analysis and modeling of the data had been conducted, and reported at various conferences. For this project the data were analyzed and modeled in more detail, and the results reported in formal journal publications. Experiments were designed and conducted as part of a multi-ship trial in the Mediterranean in 2004, using arrays with directional sensors to perform left-right discrimination. A fast forward reverberation model was developed, suitable for inversion of environmental parameters in shallow water. Towed array beam patterns were incorporated, including the effects of directional sensors; results are presented showing the effects of cardioid and limacon sensors. The model has also been extended to model echoes from targets and scattering features; preliminary comparisons with data from 2004 have been made. Future work includes a follow on JRP and clutter experiment in 2007, and extensions to the model for quantitative analysis of clutter scattering strengths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".