{"id":"W4288548696","doi":"","title":"Exploring for cobalt in Québec","year":2019,"lang":"fr","type":"other","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Cobalt; Computer science; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005660939,0.0003381904,0.0003778769,0.001433098,0.007235592,0.002654345,0.0008183039,0.0007905203,0.04058762],"category_scores_gemma":[0.0009455888,0.0001802937,0.0003395781,0.002315817,0.000884638,0.00102856,0.001214439,0.001061961,0.002552601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02776522,"about_ca_system_score_gemma":0.04653879,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9774147,"about_ca_topic_score_gemma":0.9947675,"domain_scores_codex":[0.9994937,0.00004050183,0.00001184403,0.00007476693,0.000153534,0.0002256446],"domain_scores_gemma":[0.9990761,0.00005883276,0.00004063235,0.00003465966,0.0005877072,0.0002019594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006237515,0.0003265328,0.1156166,0.001320078,0.0001570922,0.005594375,0.01254356,0.001681125,0.009214779,0.05744622,0.4592093,0.3362667],"study_design_scores_gemma":[0.00002661564,0.00007907717,0.08497466,0.0004318526,0.00004013916,0.0003552456,0.01490736,0.0009445508,0.001103808,0.001850049,0.8952506,0.00003606777],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4029819,0.01757696,0.003482144,0.06624987,0.001441016,0.0003130375,0.01169128,0.0005239195,0.4957399],"genre_scores_gemma":[0.6316735,0.006905403,0.002872189,0.004735836,0.00009324441,0.00006894716,0.003557959,0.0002034027,0.3498895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04058762,"threshold_uncertainty_score":0.2014517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03579367092994973,"score_gpt":0.2363449847631019,"score_spread":0.2005513138331521,"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."}}