DETECTION OF MESOSCALE OCEANIC FEATURES USING RADARSAT-1, AVHRR AND SEAWIFS IMAGES AND THE POSSIBLE LINK WITH JACK MACKEREL (TRACHURUS MURPHYI) DISTRIBUTION IN CENTRAL CHILE
Bibliographic record
Abstract
In order to verify the ability of RADARSAT-1 images to detect mesoscale oceanic features and the possible link of these oceanographic patterns with jack mackerel (Trachurus murphyi) distribution in the waters off central Chile, a project was developed as part of the Canada Centre for Remote Sensing Globesar-2 program. The combined use of simultaneously acquired RADARSAT-1, AVHRR sea surface temperature (SST), SeaWiFS Chlorophyll a concentration (Chl), TOPEX/ERS altimeter and ERS-2 scatterometer wind data greatly enhanced SAR imaging capabilities for the detection of oceanic features. Results show that detection of coastal wind-driven upwellings, eddies, frontal boundaries and phytoplankton blooms is possible using SAR imagery, given the proper environmental conditions. Results also suggest that jack mackerel distribution coastal resources is mainly associated with frontal boundaries, upwelling waters and high chlorophyll concentrations detected by the remotely sensing images
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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 | 0.001 | 0.000 |
| 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".