{"id":"W3035846979","doi":"10.1016/j.hydromet.2020.105395","title":"Bioleaching of arsenic-rich cobalt mineral resources, and evidence for concurrent biomineralisation of scorodite during oxidative bio-processing of skutterudite","year":2020,"lang":"en","type":"article","venue":"Hydrometallurgy","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Chemistry; Bioleaching; Arsenic; Cobalt; Mineral; Environmental chemistry; Mineral processing; Metallurgy; Inorganic chemistry; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001941006,0.0004138572,0.0002780312,0.0002848999,0.0002494676,0.0003923562,0.0002515177,0.0003124016,0.0004616527],"category_scores_gemma":[0.0002497723,0.0001407133,0.0002219408,0.000223941,0.0003628811,0.000165378,0.000329174,0.00019788,0.0001622265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003761422,"about_ca_system_score_gemma":0.000373532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004883148,"about_ca_topic_score_gemma":0.007070504,"domain_scores_codex":[0.999844,0.00002036366,0.0000115029,0.00003190139,0.00005292072,0.00003923196],"domain_scores_gemma":[0.9998723,0.00001786698,0.00003085613,0.00001098742,0.00004089481,0.00002701874],"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":[0.00007038756,0.000006105665,0.0007605015,0.0000242706,0.000002680321,0.00004807418,0.00003183739,0.00003224345,0.998659,0.00001810331,0.000004587565,0.0003421478],"study_design_scores_gemma":[0.000006703196,0.000323459,0.01390244,0.00000399543,0.00001147981,0.0001442653,0.0001348727,0.0003039041,0.9847186,0.00003488013,0.0004112378,0.000004205956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989797,0.0001404817,0.0004299255,0.00001788361,0.000002333687,0.0000102042,0.00009406541,0.000009215998,0.0003160953],"genre_scores_gemma":[0.9986455,0.000105724,0.0004737956,0.000009280418,0.00000233145,0.000008881046,0.0001292293,0.000004074866,0.0006211368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004883148,"threshold_uncertainty_score":0.009709418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05862268609528427,"score_gpt":0.2781111578222126,"score_spread":0.2194884717269284,"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."}}