Estimating channel capacity and sonar performance in the changing arctic
Bibliographic record
Abstract
Underwater acoustic processes including ambient noise, propagation, reverberation, and scattering have been studied for over half a century in the Canadian Arctic. Despite this, realistic predictions of communications and sonar performance have proved challenging due to the complex impact of ice cover on these processes, and the relative scarcity of sound speed profiles and information about the seabed. This challenge has been exacerbated in recent years because the rapid change in environmental conditions is reducing the relevance of many historical records. A key component of the present effort is to extract site specific model inputs from the environmental data contained in the literature, with an informed weighting toward more recent measurements. Site specific modelling was enhanced using inputs from recent year-long ambient noise recordings. Model inputs were also influenced by specific source and receiver hardware being developed for use in future Arctic experiments. In this paper, low frequency sonar and communication performance estimates in the frequency band 20–250 Hz, based on site-specific environmental inputs and this low frequency hardware, are presented for several geographical regions of strategic relevance in the Canadian Arctic.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".