Factors that affect water column hydrocarbon concentrations have minor impacts on microbial responses following simulated diesel fuel spills
Bibliographic record
Abstract
Effects of season and mixing on hydrocarbon concentrations and the microbial community response was explored in a series of mesocosm experiments simulating surface spills of diesel into coastal waters. Mixing of any amount contributed to hydrocarbons entering the water column, but diesel fuel composition had a significant effect on hydrocarbon concentrations. Higher initial concentrations of aromatic hydrocarbons resulted in higher water column concentrations, with minimal differences among seasons due to high variability. Regardless of the concentrations of hydrocarbons, prokaryotes increased and there were higher relative abundances of hydrocarbon affiliated bacteria with indications of biodegradation within 4 d of exposure. As concentrations decreased over time, the eukaryote community shifted from the initial community to one which appeared to be composed of organisms with some resilience to hydrocarbons. This series of experiments demonstrates the wide range of conditions under which natural attenuation of diesel fuel is an effective response.
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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".