{"id":"W2013491479","doi":"10.1016/j.electacta.2003.10.027","title":"An application of Bayesian risk theory to electrochemical processes","year":2003,"lang":"en","type":"article","venue":"Electrochimica Acta","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bayesian probability; Electrochemistry; Econometrics; Computer science; Chemistry; Artificial intelligence; Economics; Electrode; Physical chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004180459,0.0007383568,0.001354141,0.001287865,0.0006660752,0.002074148,0.001510315,0.001988937,0.003021502],"category_scores_gemma":[0.0180636,0.0007020804,0.001280238,0.001184943,0.00182212,0.00295433,0.001876798,0.002250633,0.0003274947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215038,"about_ca_system_score_gemma":0.001427591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003075802,"about_ca_topic_score_gemma":0.00232195,"domain_scores_codex":[0.99818,0.0009394966,0.00006811911,0.0001498421,0.0005606193,0.0001019886],"domain_scores_gemma":[0.9922587,0.006447628,0.00029826,0.0002851828,0.0005799227,0.0001301548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004006127,0.00004621228,0.0005040937,0.0001056257,0.00007268992,0.0001327917,0.000116234,0.2771412,0.0005291365,0.6828914,0.001440203,0.0369805],"study_design_scores_gemma":[0.00001206945,0.00002057019,0.0001891443,0.00002705792,0.00001704875,0.00006143808,0.00001557586,0.4356205,0.0001445405,0.5620607,0.001812777,0.00001868112],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006423812,0.001139092,0.9849128,0.001238151,0.00008215436,0.00001878087,0.00002972325,0.00004332307,0.006112156],"genre_scores_gemma":[0.6482148,0.005323698,0.3337666,0.0006176275,0.0007329414,0.0001661285,0.0001207103,0.00009319428,0.01096429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004180459,"threshold_uncertainty_score":0.02210867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130327127776143,"score_gpt":0.3173711410099884,"score_spread":0.3043384282323741,"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."}}