Evaluation of MODIS and SeaWiFs Ocean Color Algorithms in the Canadian Arctic Waters: The Cape Bathurst Polynya
Bibliographic record
Abstract
During the 2004 Canadian Arctic Shelf Exchanges Study (CASES) field program, an extensive in situ bio-optical data set covering the Cape Bathurst polynya was acquired. This data set was used to evaluate the performance of the OC4v4 (SeaWiFS) and OC3M (MODIS) ocean color algorithms, and to develop locally tuned ones for that region that is affected by the presence of high concentration of colored dissolved organic matter (CDOM) that contaminates the reflectance signal. The OC4v4 and the OC3M algorithms overestimated in situ chlorophyll a by roughly a factor of four. The western Beaufort sea versions of the SeaWiFS algorithm (OC4L and OC4P) provided slightly better results but still highly overestimated chlorophyll. Our new regional algorithms showed a much improved performance (MNB=5.33%) allowing for a better estimation of the chlorophyll concentration.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".