{"id":"W1474208048","doi":"10.1016/j.ifacol.2015.06.070","title":"A Predictive Preference Model for Maintenance of a Heating Ventilating and Air Conditioning System","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"HVAC; Air conditioning; Artificial neural network; Decision tree; Computer science; Filter (signal processing); Differential pressure; Reliability engineering; Machine learning; 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":[0.0001885605,0.00009639317,0.000161922,0.00002803721,0.0001152686,0.00002945187,0.0002122209,0.00003512962,2.568895e-7],"category_scores_gemma":[0.0000447953,0.00008561138,0.00003542916,0.0001419202,0.0000401603,0.0002296921,0.00009776436,0.00007313238,6.021389e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003443168,"about_ca_system_score_gemma":0.00005642234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001658117,"about_ca_topic_score_gemma":0.000007924686,"domain_scores_codex":[0.9991723,0.00001594192,0.0002202326,0.0002735384,0.0001351551,0.0001827776],"domain_scores_gemma":[0.9992945,0.00009810628,0.0001576529,0.0001913853,0.0001695649,0.00008883858],"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":[0.0001410455,0.0002528492,0.002423136,0.0007522574,0.0001199835,0.000007829191,0.0127976,0.6345977,0.01414541,0.2934143,0.0001528133,0.04119503],"study_design_scores_gemma":[0.0003765133,0.00008381988,0.000191506,0.0002133494,0.000008997096,0.00001121728,0.0004041632,0.997008,0.0003510182,0.001256424,0.00001053399,0.00008442598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1130335,0.000099081,0.8856722,0.0003532905,0.00004812276,0.0003355254,0.00005461489,0.00009481152,0.000308813],"genre_scores_gemma":[0.6134886,0.000001850879,0.3862737,0.00005076242,0.00003919298,0.00006028677,0.000007092583,0.000004786225,0.0000737268],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5004551,"threshold_uncertainty_score":0.349113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05601462601537983,"score_gpt":0.2672291153395455,"score_spread":0.2112144893241656,"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."}}