Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient
Why this work is in the frame
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Bibliographic record
Abstract
Size‐fractionated chlorophyll concentration and phytoplankton absorption spectra were compared for a wide variety of natural communities. We found that, in general, when phytoplankton abundance increases, larger sizeclasses are added incrementally to a background of smaller cells. Natural phytoplankton communities from surface waters were explicitly characterized according to their dominant cell size and taxonomic group, and the relationships between this classification and the spectral shape of the phytoplankton absorption coefficient for the whole assemblage was described. By specifying the cell size of the dominant organism (pico‐, ultra‐, nano‐, or microplankton), more than 80% of the variability in spectral shape of the phytoplankton absorption coefficient from 400 to 700 nm could be explained. This is a result of the strong covariation of the size of dominant organisms and several factors controlling the spectral shape of the phytoplankton absorption coefficient, such as pigment packaging and concentration of accessory pigments. Consequently, the shapes of phytoplankton absorption spectra can be reproduced using a spectral mixing model, where two spectra, representing the normalized phytoplankton absorption coefficients for the smallest and the largest cells found in our data set, are combined additively, using a single parameter to specify the complementary contribution of each. The differences between reproduced and measured spectra contain taxonomic and physiological information. This parameterization provides a simple tool for extracting ecological information from optical measurements. It can also be used in sensitivity analyses to describe the influence of the dominant cell size of phytoplankton on optical properties of surface waters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it