Incorporation of oil into diatom aggregates
Bibliographic record
Abstract
Rolling table experiments were conducted to investigate the incorporation of 2 types of dispersed oil into diatom aggregates. The goal was to provide specific input parameters for aggregation models that predict the transport of oil to depth via marine snow-sized aggregates (> 0.5 mm). The amount of oil incorporated into aggregates is a function of both aggregated biomass and dispersed oil concentration. The maximum carrying capacity of diatom aggregates for dispersed oil likely lies at ~40% of the aggregated organic carbon. These data allow estimates of the amount of oil routed via the aggregation pathway. Furthermore, the concentrations of transparent exopolymer particles (TEP) and the composition of EDTA-extracted extracellular polymeric substances (EPS) were tested as generally valid proxies for stickiness, which is a critical value in aggregation models. TEP and EDTA-extractable EPS were correlated with each other, but aggregation success was not readily predictable from these measurements. The large chemical heterogeneity of TEP and EPS likely obscures a generally valid relationship. Additionally, we found that, contrary to expectations, the sinking velocity of oil-containing aggregates was not decreased, but slightly increased compared to their non-oil-containing counterparts. Tighter packaging of cells due to the oil likely causes this effect. Sinking velocity is an important parameter in aggregation-sedimentation models, as it determines the time required for aggregates to reach the seafloor and thus the potential for flux attenuation. Transport of oil to the seafloor exposes benthic organisms, and those feeding on them, to substances that potentially have negative effects on organisms and ecosystems.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".