The effect of microorganisms on pulp mill effluent induced flocculation in receiving waters
Bibliographic record
Abstract
Recent studies have shown that organic matter discharged from a pulp mill flocculates and accumulates on the river bottom more rapidly than predicted by previous transport models, a phenomenon termed pulp mill effluent induced coagulation and flocculation (PMEICF). Pulp mill effluent induced coagulation and flocculation can cause accumulation of material on the river bottom that may induce anoxic or toxic conditions, subsequently harming benthic organisms and the entire food chain. Pulp mill effluent and river water were mixed in a standard jar test apparatus. Heterotrophic plate counts revealed that a variety of microorganisms was present in the floc material and the liquid portion. Individual colonies were isolated, identified, and tested for their role in flocculation. Seven isolates were found capable of enhanced flocculation: Comamonas testosteroni, species belonging to the Pseudomonas, Enterobacter, and Aeromonas genuses and an unidentified isolate. These isolates did induce flocculation, though not consistently. Results varied with the environment available for the microorganisms. Further tests are required that consider the changing effluent and river water characteristics. Key words: pulp mill effluent, coagulation, flocculation, bacteria, identification, sediment transport model.
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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 | 0.000 | 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".