{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009598886,0.0000473295,0.00006073605,0.00002450068,0.00002670681,0.00001914682,0.00001871427,0.00003051407,0.0001513262],"category_scores_gemma":[0.00003415138,0.00004581743,0.000006066702,0.00009015093,0.00001497312,0.0001449021,0.00005328501,0.00002235697,0.000002955048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002770762,"about_ca_system_score_gemma":0.000002337917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005126035,"about_ca_topic_score_gemma":0.00008952958,"domain_scores_codex":[0.9995645,0.00002250017,0.0001120265,0.000147716,0.00008037143,0.00007286054],"domain_scores_gemma":[0.999887,0.00001001675,0.00002243501,0.0000551774,0.000004635758,0.00002066692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001775333,0.00002136935,0.007187859,0.00000554768,9.920336e-7,0.000005450242,0.001716107,0.001404747,0.9857693,0.0000384828,0.000370191,0.003478129],"study_design_scores_gemma":[0.0005446411,0.00003565729,0.001063947,0.00004921908,0.000005475283,0.000009410667,0.00232155,0.3768807,0.6171368,0.0009114975,0.0008131199,0.0002278906],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937385,0.0002353236,0.001808447,0.0001138708,0.00001773012,0.00006491462,4.838458e-7,0.0000126235,0.004008149],"genre_scores_gemma":[0.9948664,0.0001231562,0.003681253,0.0001011459,0.00002583727,0.00000967163,0.0000102566,0.000004236567,0.001178058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.375476,"threshold_uncertainty_score":0.1868381,"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."}}