Satellite Remote Sensing of Herring (<i>Clupea pallasii</i>) Spawning Events: A Case Study in the Strait of Georgia
Bibliographic record
Abstract
Abstract In this proof‐of‐concept study, we show how satellite remote sensing can be used to detect and monitor Pacific herring spawning events in the Strait of Georgia (SoG), British Columbia, Canada. Multi‐sensor medium‐resolution (∼300 m) and high‐resolution (3–30 m) images reveal bright waters in the SoG due to high concentrations of herring milt from multiple spawning events. The milt‐infused waters lead to enhanced reflectance with unique spectral characteristic that can be distinguished from other optically active constituents such as suspended sediments, coccolithophores, “whiting” particles, and shallow bottoms. While the medium‐resolution images may be used to search for cloud‐free and potential spawning sites, high‐resolution images show more details in milt distributions. Given the increased availability of high‐resolution satellite imagery at the global scale, this demonstration may promote more applications of satellite remote sensing in fisheries and ocean ecology research.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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".