Production and fate of transparent exopolymer particles in the ocean
Bibliographic record
Abstract
The production and fate of transparent exopolymer particles (TEP) have been investigated in various oceanic regions (tropical, temperate, and polar), from the sea surface microlayer (SML) to the deep ocean. Accumulation of TEP within the mixed layer was observed even in the absence of phytoplankton blooms, indicating abiotic processes are important in TEP production. The abiotic TEP aggregation rates measured in the tropical and temperate North Pacific and the Arctic Ocean averaged between 8 and 12 μmol C L−1 d−1. Depth profiles from under sea ice in the Arctic revealed the highest TEP concentrations, potentially released by sympagic algal activity at the bottom of the sea ice. The aggregation rates in the SML, the interfacial layer between the ocean and atmosphere, were generally enhanced over those in the bulk surface waters by factors of 2 to 30. This finding further strengthens a developing consensus on the gelatinous nature of the SML, which will also affect microbial life, light penetration, and surface wave properties. We present a conceptual model implying that abiotic aggregation is an important factor for TEP production in the ocean, in particular in sea surface microlayers, while consumption by zooplankton and protists recycle TEP, providing a new pool of dissolved precursor material. Overall, TEP is recycled within the water column through heterotrophic grazing and degradation, providing a new pool of TEP precursor materials, while enhanced aggregation rates of TEP in the SML indicates the importance of this thin surface film in the marine carbon cycle.
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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 | 0.001 | 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".