Response of phytoplankton to eddy dipole structure in the Mozambique channel: An automated underway evaluation
Bibliographic record
Abstract
Fine-scale oceanographic structures such as eddies, fronts, and filaments strongly influence biogeochemical and ecological processes. So far, the characterization of phytoplankton communities of the Mozambique Channel (MZC) was limited to in-situ sampling and satellite monitoring of chlorophyll- a biomass estimation. Few studies have looked at phytoplankton community composition. During the RESILIENCE cruise in 2022, three structures were sampled; an anticyclonic eddy, a frontal area and a cyclonic eddy. Phytoplankton functional groups (PFGs) were studied at small-scale (1 km) in subsurface (about 5m depth) waters using automated underway measurements. A multispectral fluorometer (FLP) and an automated pulse shape-recording flow cytometer (AFCM). The oceanographic mesoscale features clearly structured the phytoplankton groups with distinct patterns observed in each of the three areas studied. A relatively high concentration of brown pigmentary group (groups containing xanthophyll and carotenoids-like pigments) was observed in the cyclonic eddy. High abundance of nano-microeukaryotes and of prokaryotic phytoplankton ( Synechococcus spp. and Prochlorococcus spp.) were identified in the cyclonic eddy. These differences could potentially affect higher trophic levels such as zooplankton, micronekton, large pelagic fish, mammals, and seabirds. Finally, this phytoplankton community differentiation could also impact biogeochemical processes such as carbon sequestration and nutrient dynamics in the MZC.
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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 | 0.001 |
| 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) | 0.000 | 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 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".