Bio-optical properties of the subtropical North Atlantic. II. Relevance to models of primary production
Bibliographic record
Abstract
Based on measurements of phytoplankton biomass, absorption coefficients and photosynthetic performance obtained from samples collected in the subtropical Atlantic Ocean, standard sets of bio-optical parameters were selected and applied to a spectral model of primary production.Computed profiles of instantaneous production, integrated over the day, and spectral irradiance were compared with measurements of 12 h in situ production and in situ spectral irradiance to assess the model's performance.Although the model performed well for the stations located on the western side of the transect, at the eastern side of the basin the model overestimated both primary production and irradiance below the mixed layer.The modelled irradiance profile was then reconciled with the observations of irradiance by increasing the assumed contribution to absorption by yellow substances.When the production model was re-implemented with the new irradiance values below the mixed layer, the computed and measured production profiles of all the stations were in good agreement.In the spectral model used in this study, the shape of the absorption spectrum of phytoplankton was used as a proxy for the shape of the photosynthetic action spectrum.Because non-photosynthetic pigments (NPPs) were abundant in pigment samples collected in the study region, the influence of NPPs on the shape of the absorption spectrum was examined and its effect on computations of primary production was quantified.When total aPh(z, h) and photosynthetic a,,(z, h) phytoplankton absorption at wavelength h and depth z were used to quantify the error resulting from failure to correct for the influence of NPPs on the shape of the absorption spectra, the results showed small errors in the computation of production at depth (up to 20%) and integrated, water-column primary production (a maximum of 10 %).
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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 | 0.000 | 0.000 |
| 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".