Applications of the Pacific Ocean Shelf Tracking System (POST): A Permanent Continental-Scale Acoustic Tracking Array for Fisheries Research&Ocean Observation
Bibliographic record
Abstract
The Pacific Ocean Shelf Tracking (POST) array was initially conceived and planned as a single continental scale acoustic tracking system for direct measurement of the marine movements and survival of animals in the ocean. With the success of the demonstration phase, POST is now transitioning into a single integrated global system of compatible arrays distributed throughout the continental shelves of all continents. Field trials in 2004 and 2005 involved the deployment of 6 major listening lines, each about 20 km long, laid out to track the migration and survival of salmon smolts along >1,200 kms of the west coast of North America. Detection rates of individual 12-16 cm long salmon smolts was >90% for a single acoustic listening line. Precise measurements of migration timing, travel speeds and survival were obtained for the freshwater and early marine phases of various salmon stocks. The results demonstrate that it is possible to measure survival and movement directly in the ocean, and that the technology can be applied to a wide range of fish species. Although a key component of the array is the ability to provide a nearly complete census of the movements and survival of marine fish such as salmon, the array concept has much broader utility and can host a wide range of other ocean sensors. Such a system would yield revolutionary advances in our ability to study the oceans. Our current efforts on the Pacific coast involve developing a permanent year-round array whose operation is less labour-intensive, more reliable, and provides this wider range of ocean observations at lower per unit cost, which will allow the deployment of a much more extensive array
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".