Operational use of ship detection to combat illegal fishing in the Southern Indian Ocean
Bibliographic record
Abstract
The Kerguelen plateau in the Southern Indian Ocean is home to the highly sought-after Patagonian Toothfish, Dissostichus eleginoides, or Chilean Sea Bass. The efficient enforcement of fishing quotas and the repression of illegal fishing activities within the French and Australian exclusive economic zones represents a significant challenge to maritime authorities due to the size and remoteness of the area. Synthetic Aperture Radar (SAR) satellites are used to detect illegal vessels, thereby allowing patrol vessels to intercept them in a much more efficient and timely manner. The SENTRY transportable groundstation from IOSAT Inc. of Halifax was upgraded and deployed on Kerguelen Island where it autonomously acquires, processes and analyses images from the Radarsat-1 and Envisat satellites. Four times per day the station automatically produces ship reports less than two hours after each pass. The ship reports are combined with Argos positions from legal vessels in order to locate illegal vessels and direct patrol vessels. The station has been in successful operation for over a year and has demonstrably contributed to the repression of illegal fishing activities
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".