{"id":"W4393350200","doi":"10.3969/j.issn.1000-6532.2022.04.024","title":"Supply Security and Technological Innovation of Global Cobalt Minerals","year":2022,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Cobalt; Metallurgy; Materials science","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":[0.0006006229,0.0002090509,0.000182351,0.001493146,0.0007364696,0.003385771,0.0002387547,0.0007625998,0.007287542],"category_scores_gemma":[0.001043696,0.0001078414,0.0002463986,0.001594729,0.00144952,0.002755251,0.001940211,0.0006280312,0.0008247804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002354662,"about_ca_system_score_gemma":0.002247359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002707791,"about_ca_topic_score_gemma":0.002341278,"domain_scores_codex":[0.9995742,0.00004732166,0.00001401616,0.00009827528,0.0001269692,0.0001390418],"domain_scores_gemma":[0.9994714,0.00008606273,0.0001664038,0.00007767841,0.0001246716,0.00007382243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000312027,0.0001254099,0.04284424,0.00075662,0.00006151936,0.001642884,0.003336028,0.004078318,0.01699817,0.7074094,0.006357388,0.216078],"study_design_scores_gemma":[0.0000650676,0.0003623204,0.09547105,0.0007205113,0.00007924042,0.001302451,0.006782115,0.00489649,0.01690118,0.1493141,0.7240551,0.00005031128],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5289872,0.01198035,0.004027163,0.01092707,0.0001392871,0.00006261583,0.0003294577,0.00008543563,0.4434614],"genre_scores_gemma":[0.970509,0.007866075,0.001051684,0.0003483932,0.00008854129,0.00002298176,0.0001466785,0.00001606503,0.01995065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007287542,"threshold_uncertainty_score":0.02437919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1522601913061991,"score_gpt":0.5102239150505603,"score_spread":0.3579637237443612,"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."}}