{"id":"W6944782844","doi":"10.21227/awav-bn36","title":"Simulated boiler data for fault detection and classification","year":2019,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Heat exchanger; Boiler (water heating); Fouling; Fault detection and isolation; Combustion; Mass flow rate; Scaling; Test data","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001114698,0.0005844906,0.0006400208,0.0003884353,0.0001719403,0.0002228455,0.001778676,0.0007927052,0.0001265403],"category_scores_gemma":[0.0005556713,0.0005970086,0.00006057299,0.0003286112,0.0001202065,0.001116158,0.0004701967,0.0005776351,0.007299895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000154833,"about_ca_system_score_gemma":0.00021445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003534515,"about_ca_topic_score_gemma":0.0006448819,"domain_scores_codex":[0.9961984,0.00008829328,0.0007523496,0.001880361,0.0005780144,0.0005025769],"domain_scores_gemma":[0.9911249,0.0002250047,0.0008570902,0.007377365,0.0002507652,0.0001648901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002019303,0.0000961028,0.000008830049,0.0003256076,0.0001639152,0.000006169165,0.000002775902,0.00005856212,0.00399094,3.286671e-7,0.9942926,0.0008522549],"study_design_scores_gemma":[0.0009559399,0.00008184379,0.0002390808,0.00007653971,0.0006504423,0.0000309411,0.00001051859,0.0212535,0.0001644265,0.000007959676,0.9758675,0.0006613393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002987047,0.00007115927,0.0005589427,0.00001524772,0.001844088,0.002020897,0.9950258,0.0001490095,0.00001619467],"genre_scores_gemma":[0.0007235699,0.0001226081,0.0001095499,0.00009622458,0.000636249,0.00007423147,0.997807,0.0001744615,0.0002561112],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02119494,"threshold_uncertainty_score":0.9996482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1492035095889044,"score_gpt":0.3719425488056409,"score_spread":0.2227390392167365,"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."}}