{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002024618,0.0003704701,0.0005641349,0.0001762301,0.0001147901,0.000215281,0.0005648653,0.0004115607,0.000335668],"category_scores_gemma":[0.0003798963,0.0003239261,0.0002093888,0.0001837301,0.000213283,0.0001766285,0.0005412473,0.0006860277,0.00003713089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008176066,"about_ca_system_score_gemma":0.00005079434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000302588,"about_ca_topic_score_gemma":0.0001364653,"domain_scores_codex":[0.9968253,0.001295471,0.0006249046,0.0005975968,0.0003690776,0.0002875839],"domain_scores_gemma":[0.9974818,0.0008163553,0.0003047937,0.0008635406,0.000344939,0.0001885698],"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":[0.00007356761,0.0007929397,0.0006841607,0.001496371,0.0006529049,0.00002569543,0.00389698,0.000283648,0.5302357,0.006647066,0.001917551,0.4532934],"study_design_scores_gemma":[0.004091734,0.000004667599,0.009533888,0.01403813,0.0005969863,0.0001188969,0.0003217458,0.3075001,0.4948691,0.0210219,0.1437327,0.004170256],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.774994,0.007607435,0.1708572,0.001619385,0.0003321908,0.000330604,0.0002450635,0.0004408225,0.04357331],"genre_scores_gemma":[0.9863105,0.001438874,0.008803206,0.00002505071,0.00003164123,0.00002071438,0.00039647,0.00006052334,0.002913045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4491232,"threshold_uncertainty_score":0.9999213,"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."}}