Initial investigation of the North East Pacific salmon feeding waters with Slocum gliders
Bibliographic record
Abstract
With the decline in the number of salmon returning to theWest Coast of Canada despite efforts to improve land-based habitat and increase hatchery releases, attention is turning to the condition of salmon ocean habitat for a reason. The offshore ocean habitat of salmon is complex and needs to be monitored continuously to facilitate an understanding of the dynamics. In preparation for long term monitoring an initial investigation was conducted to explore the suitability of ocean gliders for such a task. Three specific glider missions were executed with Slocum gliders: a long-range transit mission, a water property change mission, and a plankton bloom mission. The gliders were remotely navigated through the three missions using real-time satellite data. The long-range transit mission demonstrated successful near shore launch and recovery coupled with an extended deep sea mission. The water property change mission explored the water properties of a second year Haida Eddy. The plankton bloom mission tested the glider's ability to collect data associated with biological productivity by navigating the glider inside a second year Haida Eddy that was fertilized with iron to stimulate a plankton bloom. The data collected on the three missions is discussed in the context of images of temperature, salinity, sound velocity, water density, CDOM, and chlorophyll. These three missions demonstrated a glider's ability to collect high quality data that is requisite for understanding the dynamics of ocean waters and for developing effective management protocols for ocean salmon habitat.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".