Comparison of the Bacterial Microbiota in a Bale of Collected Cardboard Determined by 454 Pyrosequencing and Clone Library
Bibliographic record
Abstract
Biofouling, the accumulation of microorganisms, is a major problem in paper mills processing paper and cardboard. This leads to the production of lower quality recycled products. Several studies have focused on the microbial content in the paper mill and the final products. Our aim was to determine the microbial biota in a bale of collected cardboard prior to entering the paper mill. Total genomic DNA was isolated and analyzed using two different methods for comparison purposes: 454 pyrosequencing and clone library. A total of 3268 V6-V8 454 pyrosequencing reads and 322 cloned V6-V8 16S rRNA nucleotide sequences were obtained. Both methods showed the presence of three major bacterial genera: Bacillus, Solibacillus and Paenibacillus, all members of the spore-forming phylum Firmicutes. Pyrosequencing, however, revealed a richer and more diverse bacterial community than clone library. It showed the presence of additional minor Firmicute genera and of a small number of Proteobacteria. The sorting at the recycling plant, the storing, and the processing at the paper mill, the end uses, will all contribute to the bacterial microbiota present in a bale of collected cardboard as revealed here.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".