{"id":"W3170232999","doi":"10.3390/min11060606","title":"Lead Mobilization and Speciation in Mining Waste: Experiments and Modeling","year":2021,"lang":"en","type":"article","venue":"Minerals","topic":"Mine drainage and remediation techniques","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Agence Nationale de la Recherche","keywords":"Acid mine drainage; Geochemical modeling; Tailings; Environmental science; Lead (geology); Municipal solid waste; Dissolution; Drainage; Genetic algorithm; Mining engineering; Environmental chemistry; Waste management; Geology; Chemistry; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005365785,0.0005879018,0.0007164658,0.0004016294,0.0004058948,0.000575523,0.0009446609,0.001143248,0.0006999266],"category_scores_gemma":[0.0006420699,0.0002570704,0.0006149368,0.0007310681,0.0003611145,0.0005111967,0.0004822834,0.0004966477,0.0001590896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007952228,"about_ca_system_score_gemma":0.0005612462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008219273,"about_ca_topic_score_gemma":0.004533421,"domain_scores_codex":[0.9998228,0.00002782291,0.00001630115,0.00004204586,0.00005768391,0.00003335688],"domain_scores_gemma":[0.9996645,0.000199262,0.00003922642,0.00002538713,0.00005966809,0.00001189814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006123964,0.0008944012,0.01218037,0.0009438393,0.00006737262,0.001053626,0.0003122276,0.7998517,0.1680365,0.003564522,0.0004670143,0.01201611],"study_design_scores_gemma":[0.00009318339,0.000531754,0.001721759,0.00001719306,0.00003494563,0.00009663072,0.00009942239,0.9216421,0.07378785,0.00101931,0.000929723,0.00002622034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885444,0.0004556267,0.007320825,0.000148039,0.00002012429,0.0001317759,0.0007415503,0.00007339976,0.002564104],"genre_scores_gemma":[0.9918228,0.0007945367,0.00577154,0.00002863194,0.00001201939,0.0001686002,0.0002525799,0.000009962682,0.001139315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008219273,"threshold_uncertainty_score":0.01634288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02705036235884719,"score_gpt":0.2721845132078886,"score_spread":0.2451341508490414,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}