Elimination du zinc par les cosses de petits pois (<i>Pisum sativum</i>) et les feuilles de lierre (<i>Hedera helix L</i>) Elimination of zinc by peapods (<i>Pisum sativum</i>) and ivy leaves (<i>Hedera helix L</i>)
Bibliographic record
Abstract
Résumé La pollution des eaux souterraines et de surface par les métaux lourds constitue un grand problème pour l'environnement ; de ce fait il s'avère nécessaire de pouvoir éliminer ces substances toxiques. Il existe de nombreuses méthodes qui permettent d'éliminer ces dernières, telles que l'adsorption, la précipitation chimique et la filtration sur membrane. Dans notre étude, le zinc a été adsorbé sur les cosses de petits pois et les feuilles de lierre. Un temps de réaction de 30 minutes a été obtenu pour les deux adsorbants ; ainsi qu'un pH optimal égal à 4 pour les feuilles de lierre et à 5 pour les cosses de petits pois. Les résultats obtenus montrent également que les isothermes d'adsorption sont de type I.
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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".