Testing the feasibility of a concurrent comparison of continuous and pulsed active sonar
Bibliographic record
Abstract
The performance of continuous active sonar (CAS) was compared to conventional pulsed active sonar (PAS) during the TREX13 (Target and Reverberation Experiment 2013) sea trial. The approach was to execute a one-hour CAS run followed closely by a one-hour PAS run to limit the environmental variability between runs and allow a fair comparison. This approach was possible because the sonar source and receiver were fixed to the seabed. A different approach was required for a more recent sea trial, LCAS15 (Littoral Continuous Active Sonar 2015), where the source and receiver were towed from a ship. Ship motion increases variability in sonar performance, therefore a simultaneous comparison of CAS and PAS was desired so that any motion effects were the same for both waveforms. The approach of transmitting CAS and PAS concurrently in two separate frequency bands was taken. The risk with this approach is that potential differences in propagation in the two bands could bias the comparison. A run in which equivalent CAS waveforms were transmitted simultaneously in the two bands was therefore performed to establish a baseline for the performance difference between the bands. Doppler-corrected replicas were required in all of the correlation processing due to the high Doppler sensitivity of the long-duration, wideband CAS waveforms. Preliminary results from the LCAS15 sea trial will be presented.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".