{"id":"W4299441299","doi":"","title":"Recovery of zinc, manganese and lead from pyrometallurgical sludge by hydrometallurgical processing","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Manganese; Metallurgy; Zinc; Pyrometallurgy; Lead (geology); Environmental science; Materials science; Smelting; Geology","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":[0.0001278696,0.0001987644,0.0002758768,0.0002452846,0.0002231964,0.0003739774,0.0001403854,0.0003104492,0.001077193],"category_scores_gemma":[0.0001727785,0.0001110604,0.0002300604,0.0001514943,0.0001853957,0.0002061937,0.0002108195,0.0002538999,0.0005649506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002897923,"about_ca_system_score_gemma":0.0003325072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001648149,"about_ca_topic_score_gemma":0.004078225,"domain_scores_codex":[0.999938,0.000006891337,0.000003838483,0.00001445072,0.0000224753,0.00001426534],"domain_scores_gemma":[0.9999592,0.000008479661,0.000006546908,0.000004878403,0.00001389576,0.000006892174],"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":[0.0001971935,0.00002738522,0.0003177786,0.0000511179,0.000003068938,0.0000515914,0.00003094514,0.0004081552,0.9946515,0.00004867918,0.00005018047,0.004162445],"study_design_scores_gemma":[0.000009229042,0.00009709461,0.001264555,0.00000436291,0.000006722857,0.00003912034,0.00002820644,0.00111453,0.9967586,0.00006040707,0.0006145251,0.000002463051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945343,0.0002885273,0.003342692,0.00009570161,0.0000208176,0.00001391953,0.00009738295,0.00004125003,0.001565416],"genre_scores_gemma":[0.9912366,0.0002668491,0.002185351,0.00003126186,0.000006778582,0.000006126485,0.0001020722,0.00002104551,0.006144012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001648149,"threshold_uncertainty_score":0.003603637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185524506570986,"score_gpt":0.2154135690542429,"score_spread":0.2035583239885331,"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."}}