Twenty years of satellite observations describing phytoplankton blooms in seas adjacent to Gwaii Haanas National Park
Bibliographic record
Abstract
Abstract. Visible satellite imagery is used to estimate the variability of chlorophyll concentration and “brightness ” events in surface waters within and adjacent to the proposed National Marine Conservation Area associated with the Gwaii Haanas National Park Reserve and Haida Heritage Site in northern British Columbia, Canada. We examine ocean colour imagery from the coastal zone colour scanner (CZCS; 1979–1985) and sea-viewing wide field-of-view sensor (SeaWiFS; 1998– 2000) and visible imagery from the advanced very high resolution radiometer (AVHRR; 1982–2000) to document variability in these parameters because few ship-based observations of phytoplankton exist for this region. The AVHRR imagery indicates that large bright surface patches occur in most summers on the east coast but not the west coast of the Gwaii Haanas National Marine Conservation Area (GHNMCA). The bright patches originate from three main sources: Dogfish Bank to the north, Queen Charlotte Sound to the south, and within the GHNMCA. The ocean colour data reveal large potential interannual variations in satellite-derived chlorophyll for three regions in the GHNMCA and indicate that the Hecate region typically has the highest estimated chlorophyll. Seasonally, all three regions show a bimodal pattern in chlorophyll concentrations, with a spring peak in April–May and a second peak in August–September. At present, few field samples exist to verify the phytoplankton species or seasonal trends in chlorophyll identified by satellite sensors. Résumé. Les images satellitaires dans le visible ont été utilisées pour évaluer la variabilité de la concentration de chlorophylle et les événements de « brillance » dans les eaux de surface à l’intérieur et à proximité de la Zone de
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".