{"id":"W4232765708","doi":"10.32920/ryerson.14649315.v1","title":"Design and implementation of intelligent building / smart building","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Building automation; Architectural engineering; Building management; Building design; HVAC; Function (biology); Service (business); Work (physics); Sophistication; Facility management; Building management system; Risk analysis (engineering); Computer science; Engineering management; Engineering; Systems engineering; Business; Artificial intelligence","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":[0.0001320702,0.0001643769,0.0002053756,0.00009949068,0.00002517739,0.0000480932,0.00007042941,0.0001040651,0.00005176692],"category_scores_gemma":[0.00001620182,0.0001799778,0.00003210017,0.00004361712,0.00001583478,0.00005304554,0.0001602031,0.000180251,2.335677e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006424545,"about_ca_system_score_gemma":0.00001956295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005609011,"about_ca_topic_score_gemma":0.000006794432,"domain_scores_codex":[0.999272,0.00001988569,0.0002809596,0.0002032744,0.00009056921,0.0001333348],"domain_scores_gemma":[0.9996125,0.00007001713,0.00006540894,0.000165863,0.00004957224,0.00003666408],"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":[0.00000135326,0.00000338278,0.0000337703,0.0002768697,0.00004322348,0.000001299439,0.0002120122,0.9835538,0.002305705,0.000580038,0.00001979992,0.01296877],"study_design_scores_gemma":[0.0001147719,0.00001617707,0.0001518733,0.0001349764,0.00005073752,0.00000295399,0.0003972867,0.4252833,0.5708074,0.002688207,0.00007783638,0.0002745206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03928339,0.0004875418,0.9594114,0.000008277213,0.0003273465,0.0002183763,0.00000336898,0.0001513066,0.0001089278],"genre_scores_gemma":[0.5597425,0.0006561277,0.4395181,0.000003844243,0.00001748505,0.00001301622,0.00002274952,0.00001893907,0.0000072927],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5685017,"threshold_uncertainty_score":0.7339281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421569252988296,"score_gpt":0.2884179541677153,"score_spread":0.2642022616378323,"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."}}