{"id":"W2040496500","doi":"10.1016/j.hydromet.2006.09.001","title":"Modelling zinc heap bioleaching","year":2006,"lang":"en","type":"article","venue":"Hydrometallurgy","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chemistry; Bioleaching; Heap (data structure); Heap leaching; Hydrometallurgy; Zinc; Process engineering; Metallurgy; Copper; Algorithm; Engineering; Computer science","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":[0.0002133141,0.0006118719,0.001014249,0.0005034061,0.0006815594,0.00135559,0.001567409,0.002814293,0.007922572],"category_scores_gemma":[0.001164233,0.0007495403,0.0009172873,0.0005660011,0.0009878357,0.0009791557,0.0008051429,0.0007155304,0.000607668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00177619,"about_ca_system_score_gemma":0.001769299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04806754,"about_ca_topic_score_gemma":0.02520816,"domain_scores_codex":[0.9998707,0.00001905875,0.000004730985,0.00003167744,0.00003184178,0.00004193934],"domain_scores_gemma":[0.9995746,0.0002640254,0.00003810673,0.0000244849,0.00006166379,0.00003720383],"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":[0.00001792486,0.00001327114,0.000196379,0.00002039392,0.000005608907,0.00004027256,0.000009943281,0.9967955,0.0006189715,0.001366327,0.00009339926,0.00082207],"study_design_scores_gemma":[0.00001690315,0.00001261317,0.0001264359,0.000002996221,0.000005014196,0.000009381672,0.00001313839,0.9978319,0.0005116805,0.0009334234,0.0005319924,0.000004535369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7732739,0.0008931537,0.14186,0.0009963916,0.0001552394,0.0002087063,0.001987719,0.001102408,0.07952254],"genre_scores_gemma":[0.9720462,0.0003230548,0.01063421,0.00006800584,0.00001193806,0.0001132071,0.0003623187,0.0001203186,0.0163208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04806754,"threshold_uncertainty_score":0.09557551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307063475544587,"score_gpt":0.1955655725941194,"score_spread":0.1824949378386736,"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."}}