{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006432018,0.0001516986,0.0003634618,0.0003377067,0.0001504722,0.0002262812,0.000712957,0.00007503686,0.005187439],"category_scores_gemma":[0.0001797827,0.0001517761,0.00004335708,0.001808629,0.00008835385,0.001011113,0.0003513562,0.0003090791,0.000001970719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009025278,"about_ca_system_score_gemma":0.00005180915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007750429,"about_ca_topic_score_gemma":0.00002405774,"domain_scores_codex":[0.998539,0.00007666315,0.0006428939,0.0001822118,0.0003999483,0.0001592872],"domain_scores_gemma":[0.9991584,0.00008300137,0.0003171534,0.0001642836,0.0002179538,0.00005921588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001622809,0.0003537743,0.4231924,0.000286056,0.0001870268,0.0000223911,0.0001982284,0.007191326,0.4166409,0.0108551,0.1293002,0.01161034],"study_design_scores_gemma":[0.00149959,0.00005623133,0.6073161,0.000168575,0.000092044,0.0001802117,0.0008348679,0.003146622,0.1149379,0.07430785,0.1964869,0.0009730289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808095,0.006988607,0.0003824633,0.0002009197,0.0002565492,0.0002187882,0.0001175751,0.00009598317,0.01092969],"genre_scores_gemma":[0.9974868,0.002079208,0.0001161521,0.0001175145,0.00002631841,0.00003569574,0.00001863141,0.00001305912,0.0001066218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.301703,"threshold_uncertainty_score":0.9957219,"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."}}