{"id":"W6907129349","doi":"10.21227/8tq1-wy17","title":"Simulated Boiler Fault Data","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":"Boiler (water heating); MATLAB; Fault (geology); Time series; Training set; 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","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001413711,0.001236076,0.001433935,0.0005704021,0.0001357604,0.0003070791,0.01095269,0.00119198,0.006669168],"category_scores_gemma":[0.0005643442,0.001209804,0.0001482528,0.0007787354,0.0002089551,0.001504438,0.003261643,0.001865496,0.4025809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002068538,"about_ca_system_score_gemma":0.0008436679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00227635,"about_ca_topic_score_gemma":0.0005309428,"domain_scores_codex":[0.9924332,0.0001841562,0.001278353,0.003026628,0.00185626,0.001221385],"domain_scores_gemma":[0.9717311,0.0002059884,0.001059708,0.0263657,0.0002439154,0.0003936242],"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":[0.00008964318,0.0002768955,0.0000246973,0.0002358117,0.0004678489,0.000646074,0.000003229074,0.0003218778,0.0001073119,2.172528e-7,0.9977649,0.00006143721],"study_design_scores_gemma":[0.0008974308,0.00004574439,0.00003858086,0.0001918799,0.0007868586,0.00008591009,0.000005634656,0.0008881305,0.00003287895,0.000003258393,0.9955897,0.001433933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006522694,0.0001397557,0.000007315667,0.00002111688,0.004704068,0.001116598,0.9933745,0.0003249802,0.0002464743],"genre_scores_gemma":[0.00002652742,0.0001309881,0.00006411302,0.0005603639,0.001328547,0.00001331835,0.9954884,0.0003857213,0.002001991],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3959118,"threshold_uncertainty_score":0.9990352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1452184770523037,"score_gpt":0.3803540089786478,"score_spread":0.2351355319263441,"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."}}