Beam attenuation, scattering and backscattering of marine particles in relation to particle size distribution and composition in <scp>H</scp>udson <scp>B</scp>ay (<scp>C</scp>anada)
Bibliographic record
Abstract
Abstract This study investigated the relationships between the concentration of biogeochemical parameters and particulate beam attenuation (cp), scattering (bp), and backscattering (bbp) in Hudson Bay. Results showed that most of the variability resulted from the presence of a deep chlorophyll maximum. cp, bp, and bbp were all adequate proxies to estimate total suspended matter (TSM) but were mostly sensitive to particulate inorganic matter (PIM) in the surface layer, and particulate organic matter (POM) at the chlorophyll maximum depth. The backscattering ratio varied in the range of 0.005–0.05 and was inversely related to the POM : TSM ratio. According to the Twardowski et al. (2001) model, the PSD slope ξ well represented and bulk refractive index in relation to particulate composition. For inorganic particulate dominated waters, both and had a larger range and a higher mean value than at organic particulate dominated waters. This knowledge on the optical properties related to the PSD and particulate composition provides valuable information for further investigation and broadens our understanding of ocean optics in high latitude waters leading to potential improvements of regional scale remote sensing algorithms.
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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 | 0.000 | 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".