{"id":"W2171510151","doi":"","title":"Extended Abstract: Estimation of froth quality using Bayesian information synthesis","year":2011,"lang":"en","type":"article","venue":"International Symposium on Advanced Control of Industrial Processes","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Syncrude (Canada)","funders":"","keywords":"Computer science; Fuse (electrical); Soft sensor; Extraction (chemistry); Process (computing); Process engineering; Quality (philosophy); Oil sands; Sampling (signal processing); Data mining; Information extraction; Asphalt; Real-time computing; Engineering; Artificial intelligence; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002431833,0.0001757574,0.0003393978,0.0001828069,0.00003210219,0.00002349878,0.0002274259,0.000150813,0.00009160727],"category_scores_gemma":[0.0006975208,0.0001716738,0.00008452476,0.0001768437,0.00003938542,0.0008488713,0.000008209338,0.0001449291,0.000007189159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001059017,"about_ca_system_score_gemma":0.00006219525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001534599,"about_ca_topic_score_gemma":0.000009117084,"domain_scores_codex":[0.9983829,0.0000293487,0.000917072,0.00012373,0.0004064136,0.000140548],"domain_scores_gemma":[0.9987131,0.000224806,0.0005123868,0.0001505013,0.0003445804,0.00005464333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003064624,0.0002809181,0.0005942157,0.0004422332,0.000537038,0.000001909691,0.0006997157,0.7155901,0.0886007,0.001613342,0.00002662592,0.1885486],"study_design_scores_gemma":[0.008204068,0.0003060645,0.001444049,0.0009574388,0.0001130713,0.000009828003,0.0005171351,0.3718962,0.6142499,0.0007737234,0.0009198569,0.0006086631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6483145,0.0001622697,0.3032805,0.0002453828,0.004365927,0.001763648,0.0005947231,0.0005642465,0.04070884],"genre_scores_gemma":[0.9993095,0.00001417389,0.0004541611,0.00002334993,0.0001053275,0.00006155205,0.000009361254,0.00001584347,0.000006766876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5256492,"threshold_uncertainty_score":0.7000655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812208841741393,"score_gpt":0.2661165206244606,"score_spread":0.2379944322070466,"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."}}