{"id":"W2767223182","doi":"10.1016/j.jobe.2017.10.013","title":"A practical solution for HVAC prognostics: Failure mode and effects analysis in building maintenance","year":2017,"lang":"en","type":"article","venue":"Journal of Building Engineering","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; National Research Council Canada","funders":"","keywords":"HVAC; Prognostics; Reliability engineering; Failure mode and effects analysis; Engineering; Fault detection and isolation; Work (physics); Fault (geology); Computer science; Risk analysis (engineering); Air conditioning; Artificial intelligence; Mechanical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0003801911,0.0001545409,0.000330822,0.0004136171,0.0000994674,0.000140302,0.0001599445,0.0001094536,6.2678e-7],"category_scores_gemma":[0.0006223649,0.0001533777,0.0001143776,0.0001658154,0.00001656155,0.0005493024,0.00003613759,0.0002737687,3.768451e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054822,"about_ca_system_score_gemma":0.00001661792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007317877,"about_ca_topic_score_gemma":0.00001167768,"domain_scores_codex":[0.9991289,0.000008858708,0.0003316346,0.0001239968,0.0001386433,0.0002679195],"domain_scores_gemma":[0.9993065,0.0001950209,0.0001743154,0.0001688327,0.00007431471,0.00008101204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001533681,0.0000119793,0.001261651,0.0001464673,0.0002110116,0.00001947014,0.00003939751,0.9812129,0.0141791,0.00178962,0.0001137764,0.00099926],"study_design_scores_gemma":[0.0005308853,0.00004207644,0.002562115,0.0003144797,0.000202724,0.00005027014,0.000005195443,0.9913523,0.004211888,0.0002708038,0.0002891393,0.000168084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2666189,0.0001576884,0.7326739,0.0001523417,0.000262471,0.00008464341,0.000001346051,0.00004091001,0.000007781304],"genre_scores_gemma":[0.7288377,0.00006307758,0.2709367,0.000004910033,0.0001192205,0.0000101336,7.032519e-7,0.00002394849,0.000003550333],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4622189,"threshold_uncertainty_score":0.625456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008337461997711626,"score_gpt":0.2599226580734746,"score_spread":0.251585196075763,"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."}}