{"id":"W2782788408","doi":"10.1016/j.hydromet.2018.01.001","title":"Temperature control in copper heap bioleaching","year":2018,"lang":"en","type":"article","venue":"Hydrometallurgy","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Raffinate; Heap leaching; Heap (data structure); Bioleaching; Chemistry; Copper; Metallurgy; Chalcocite; Volumetric flow rate; Hydrometallurgy; Sulfide; Thermodynamics; Materials science; Chalcopyrite; Extraction (chemistry); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002913201,0.0001782207,0.0002398236,0.0002239219,0.00006724368,0.00005643065,0.0001287716,0.0001292285,0.0004844118],"category_scores_gemma":[0.0000315071,0.0001546794,0.00007630631,0.0002934827,0.00004358473,0.0001939925,0.00001444211,0.0003605363,0.0005980509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004965321,"about_ca_system_score_gemma":0.000008549881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003732959,"about_ca_topic_score_gemma":0.00008509896,"domain_scores_codex":[0.999051,0.00005532787,0.0002524942,0.0001976714,0.0001350968,0.0003084588],"domain_scores_gemma":[0.9996352,0.00003655836,0.00002239367,0.0001961681,0.00001733042,0.00009240911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002427803,0.0000618896,0.0005445345,0.00003766,0.00008158269,0.00003003154,0.0002585098,0.002987955,0.9831059,0.0008884462,0.001695744,0.01028347],"study_design_scores_gemma":[0.004155912,0.0003354606,0.01469269,0.0002625181,0.00006059346,0.0002519097,0.000273638,0.2806332,0.035754,0.0005877264,0.6612928,0.001699531],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373408,0.000368315,0.0009307231,0.0001606374,0.0009963105,0.000144464,0.00000481815,0.0003740738,0.05967985],"genre_scores_gemma":[0.9982584,0.00002850681,0.0003268814,0.0004778288,0.0002978274,0.000009930479,0.000008934962,0.00003239962,0.0005592718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9473519,"threshold_uncertainty_score":0.7686934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006281762127987247,"score_gpt":0.2114086643030886,"score_spread":0.2051269021751013,"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."}}