Decoloration of Amaranth by the white-rot fungus<i>Trametes versicolor</i>. Part I. Statistical analysis
Bibliographic record
Abstract
The white-rot fungus Trametes versicolor decolorized the mono-azo-substituted naphthalenic dye Amaranth. The relationship between the amount of enzymes present in the system and the efficiency of the decoloration process was investigated. The two responses used to quantify the process of decoloration (i.e., initial decoloration rate, v0, and the percent concentration of dye decolorized in 1 h, %c) were correlated with the amount of three enzymes considered for the study (lignin peroxidase, manganese peroxidase, and laccase) and analyzed through stepwise regression analysis (forward, backward, and mixed). The results of the correlation analysis and those of the regression analysis indicated that lignin peroxidase is the enzyme having the greatest influence on the two responses.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".