Physical and chemical factors affecting microbial biomass and activity in contaminated subsurface riverine sediments
Bibliographic record
Abstract
Over 80 years of direct discharge of industrial effluents into the Mahoning River, located in northeastern Ohio, USA, has led to the accumulation of a wide variety of pollutants within its sediments. This study examined the physical and chemical parameters, including lipophilic pollutants, affecting microbial activity and biomass in subsurface (10-40 cm horizon) sediments. Microbial biomass was higher in anthropogenically contaminated sediments, and step-wise linear regression showed that approximately 82% of the variation in microbial biomass could be explained by total hexane extractable hydrocarbons, sediment particle size, and water content. There was no correlation between microbial activity and biomass. Independent variables influencing anaerobic activity were temperature and water holding capacity. The results of this study indicate that freshwater, sedimentary anaerobic microbial communities respond to a range of environmental parameters, many of which influence subsurface river sediments, and that lipophilic pollutants, when present, can cause increases in total microbial biomass.
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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) | 0.000 | 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".