Recommandations sur l’utilisation des outils de prédiction du drainage minier acide
Bibliographic record
Abstract
The sulphidic tailings subjected to the atmospheric water and oxygen action may generate acid mine drainage (AMD). AMD is due to the oxidation of sulphide minerals they contain in the absence of a neutralizing potential. The effluents related to AMD are acidic, metal loaded and are often harmful towards the surrounding environments. A reliable prediction of this phenomenon to preserve the environment is of great importance as it is able to impact the costs and the ways to restore mines sites. The most frequently tools used for AMD prediction are static tests and kinetic tests when the first provide uncertain prediction results. AMD perdition tests are available in several versions whose protocols are quite divergent. Also, there is no guide orientating users in their choice. Thus, the objective of this review paper is to give clear recommendations to help choosing among either static and kinetic tests for AMD prediction based on tailings intrinsic characteristics (for static tests) and on the objectives of the study (for kinetic assays). Les rejets miniers sulfurés soumis à l’action de l’eau et de l’oxygène atmosphériques sont susceptibles de générer du drainage minier acide (DMA) suite à l’oxydation des minéraux sulfurés qu’ils contiennent, en l’absence d’un potentiel neutralisant. Les effluents acides liés au DMA peuvent être chargés en métaux et sont dommageables à l’environnement. Une prédiction fiable de ce phénomène est d’une grande importance car elle est capable de déterminer les coûts et la manière de restaurer les sites miniers pour préserver l’environnement. Les outils usuellement utilisés pour la prédiction du DMA sont les tests statiques dans un premier temps et les essais cinétiques quand les premiers livrent une prédiction incertaine. Ces outils sont nombreux, leurs protocoles sont assez distincts et il n’existe aucun guide pour orienter l’utilisateur dans leur choix. Ainsi, ce papier se fixe l’objectif de présenter des recommandations pour orienter le choix parmi les tests statiques et et les essais cinétiques. Ces outils sont utilisés par l’industrie minière pour la prédiction du DMA en se basant sur les caractéristiques intrinsèques des rejets miniers (tests statiques) et des objectifs de l’étude (essais cinétiques).
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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 | 0.048 | 0.114 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".