Seasonal variability of light absorption properties and water optical constituents in Hudson Bay, Canada
Bibliographic record
Abstract
Previous studies have shown that the properties of optically significant water constituents (phytoplankton, suspended matter, and colored dissolved organic matter (CDOM)) in Hudson Bay are different from other Arctic regions. A new bio‐optical data set collected in summer 2010 shows that this region also presents seasonal variability of the light absorption coefficients by the different constituents, with a higher relative proportion of CDOM absorption in summer than in the fall as a result of decreased phytoplankton absorption in summer. The slope of the exponential function describing nonalgal particles and CDOM spectral absorption shows little variability between fall and summer. Seasonal variability of light absorption coefficients and water optical constituents is more pronounced near the coast, while less variability is observed in the central part of the bay. Very low summertime chlorophyll‐specific absorption coefficients by phytoplankton, among the lowest reported in the literature, are attributed to the high proportion of large size phytoplankton (microphytoplankton) and important packaging effect. There is also a smaller contribution of accessory pigments to total pigments in the summer than in the fall, resulting in a lower blue‐to‐red phytoplankton absorption ratio. These results emphasize that it is necessary to take into account the seasonal variability of light absorption properties in bio‐optical models for further remote sensing applications in Hudson Bay.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".