A two‐component model of phytoplankton absorption in the open ocean: Theory and applications
Bibliographic record
Abstract
The two‐population absorption model of Sathyendranath et al. is extended to retrieve the specific absorption coefficients (absorption per unit concentration of chlorophyll‐a) of the component populations of phytoplankton. The model relates the absorption coefficient of phytoplankton to chlorophyll‐a concentration, assuming that the assemblages of phytoplankton comprise mixtures of two populations whose proportions vary as the total concentration of cells changes. The model is applied to in situ data collected from six regions during 34 cruises. The model compares well with earlier models of phytoplankton absorption but brings the additional advantage of parameters that have clear bio‐optical and biological interpretation. Size structure of the phytoplankton populations was inferred from the values of the specific absorption coefficients. The results are consistent with pigment analyses performed on the same samples. Seasonal analysis of data from the northwest Atlantic, southeast Pacific, and the Arabian Sea showed significant changes in the spectral form and magnitude of the specific absorption coefficients of small‐ and large‐celled populations, which appear to be related to changes in species composition. The model serves thus as an optical tool to explore the large‐scale biogeography of phytoplankton.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".