Influence de la matière organique et inorganiquede l'eau sur l'élimination des pesticides par nanofiltration
Bibliographic record
Abstract
Ce travail explore les performances de deux types de membranes de nanofiltration (Desal DK et NF200) dans l'élimination dans les eaux de certains pesticides (l'atrazine et son métabolite la déséthylatrazine (DEA), la simazine, la cyanazine, l'isoproturon et le diuron) et évalue l'influence de la présence de matière organique ou inorganique dans la matrice d'eau sur l'efficacité de ce traitement. Des eaux synthétiques, composées à partir d'eau distillée à laquelle a été ajoutée de la matière organique (acides humiques) ou inorganique (CaCl2 ou CaSO4), ont été traitées sur un pilote de nanofiltration durant 96 heures. Les taux rétention en pesticides et ceux de leur adsorption sur les membranes ont été calculés et comparés aux résultats obtenus sur une matrice d'eau distillée pure. Une influence du type de membrane et de la présence de la matière humique sur le taux d'abattement de certains pesticides a été constatée. L'influence de la matière inorganique est pratiquement insignifiante.
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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 | 0.000 | 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".