A survey of the composition and diversity of bacterial populations in bleached kraft pulp-mill wastewater secondary treatment systems
Bibliographic record
Abstract
Bacterial community compositions from 10 pulp- and paper-mill treatment systems were compared using both traditional and molecular techniques. 16S-RFLP (Random Fragment Length Polymorphisms) analysis was used to examine the genotypic profiles of the whole bacterial community of each treatment system. Although all the communities shared approximately 60% of their DNA band pattern, as determined by computer-assisted cluster analysis, each community displayed a unique profile that was stable over time under normal operating parameters. Reverse Sample Genome Probing (RSGP) and 16S-RFLP were used to compare the culturable bacterial communities of several geographically separated pulp-mill biotreatment system communities. There was little overlap in the composition of the culturable community between mills at the genus level. Furthermore, RSGP variation was almost as high within a mill as between mills. Partial sequences of the 16S rRNA genes from culturable isolates identified Bacillus spp., Pseudomonas spp., and Xanthobacter as some of the dominant species. Finally, several 16S rRNA genes from two whole community 16S RNA gene libraries were partially sequenced and identified as similar to unknown alpha-, beta-, and gamma-Proteobacteria, Ralstonia, Alcaligenes, Nitrospira, Firmicutes, and clones representing the new Holophaga/Acidobacterium phylum. These findings suggest that although these pulp- and paper-mill biotreatment communities perform similar functions, they are populated by unique mixtures of species.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".