Extracellular proteins produced by different species of the fungus Trichoderma on a secondary paper mill sludge substrate
Bibliographic record
Abstract
Kraft pulping is the most commonly used pulping process in the pulp and paper industry. In this process wood chips are chemically delignified using sodium sulfide and sodium hydroxide. Delignification is usually followed by mechanical fiberization and a bleaching process of the resulting wood pulp. In addition to lignin-free wood pulp, this process also produces waste that contains residues of used chemicals, lignin, cellulose, hemicelluloses, and small amounts of other wood components. Because of the worldwide large-scale production of paper, the sludge from paper mills contributes significantly to environmental pollution. Although there have been great efforts being made to utilize this lignin-rich material, sludge is mostly disposed in landfills or incinerated in a boiler. This research project used secondary sludge as a substrate for 7 wood-decay fungi taxonomically belonging to the genus Trichoderma. The examined fungi expressed the capability of consuming sludge components as a carbon source to produce extracellular proteins. The proteins were separated by gel electrophoresis. Before and after fungi cultivation, the sludge was analyzed by Fourier transform infrared spectroscopy (FTIR).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".