Composition of the bacterial biota in slime developed in two machines at a Canadian paper mill
Bibliographic record
Abstract
During the process of papermaking by pulp and paper plants, a thick and viscous deposits, termed slime, is quickly formed around the paper machines, which can affect the papermaking process. In this study, we explored the composition of the bacterial biota in slime that developed on shower pipes from 2 machines at a Canadian paper mill. Firstly, the composition was assessed for 12 months by DNA profiling with polymerase chain reaction coupled with denaturing gradient gel electrophoresis. Except for short periods (2-3 months), clustered analyses showed that the bacterial composition of the slime varied substantially over the year, with less than 50% similarity between the denaturing gradient gel electrophoresis profiles. Secondly, the screening of 16S rRNA gene libraries derived from 2 slime samples showed that the most abundant bacteria were related to 6 lineages, including Chloroflexi, candidate division OP10, Clostridiales, Bacillales, Burkholderiales, and the genus Deinococcus. Finally, the proportion of 8 bacterial lineages, such as Deinococcus sp., Meiothermus sp., and Chloroflexi, was determined by the Catalyzed Reporter Deposition-Fluorescence In Situ Hybridization in 2 slime samples. The results showed a high proportion of Chloroflexi, Tepidimonas spp., and Schlegelella spp. in the slime samples.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".