Potential of <i>Pseudomonas yamanorum</i> for the valorization of municipal biosolids
Bibliographic record
Abstract
Abstract It is generally accepted that some trace organic contaminants (TrOCs) pass through the wastewater treatment process without being properly treated and find their way into waterbodies. These molecules can also be concentrated within the biosolids (BS) through adsorption. The presence of TrOCs in BS, which are then commonly used as soil amendments in agriculture, may affect plant growth and viability. The potential risks posed by TrOCs are usually ignored because they are present in low concentrations and mostly have relatively short half-lives. However, the continuous addition of these substances in water sources and on farmlands makes them pseudo-persistent. To reduce the concentrations of selected TrOCs from these BS, Pseudomonas yamanorum LBUM636 (PY) was tested with and without a commercial bacterial blend of Bacillus spp. (BC). About 60% removal of atrazine was achieved using PY-amended BS. Bioslurries inoculated with PY had relatively high laccase activity at about 2,200 U/L. Laccase activity was seven times higher in samples where BC was also present, which suggests a synergistic effect between BC and PY. Concentrations of phenazine-1-carboxylic acid, an antibiotic with a biopesticide effect, were also relatively important in PY-inoculated bioslurries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".