Development of quality criteria based on a toxicological characterization of fertilizing residuals
Bibliographic record
Abstract
Toxicity tests were used to evaluate the environmental toxicity of municipal and industrial residuals compared to cow and hog manures. The goal was to evaluate the impact of chemicals that are either potentially present but not routinely analyzed, or unknown. Four toxicity tests were used: germination and growth of barley (Hordeum vulgare), mortality of Daphnia magna, light production inhibition of the bioluminescent bacteria Vibrio fischeri, and mortality of earthworms (Eisenia andrei). Twenty-five samples of residuals and 20 samples of manures were sampled and mixed into standardized soil samples. Part of the amended soil was used for barley tests whereas a water extract of the rest was used for toxicity tests with Daphnia and Vibrio. The worm tests were performed with fertilizing residuals and manures not mixed with soil. The toxicity varied according to the amount of manure or fertilizing residual added to the soil samples. At agronomic rates, toxicity of most of the residuals was low or even negative (stimulation of barley growth). A set of toxicological tests and criteria is proposed to assess if a given residual presents an elevated toxicity as compared to that of manures. Results of this study were used by the Ministère du Développement durable, de l'Environnement et des Parcs (MDDEP) to establish toxicity criteria in its guidelines for the valorization of fertilizing residuals. Key words: biosolid, sludge, lime residuals, toxicity test, manure, residual, toxicity, criteria.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".