{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005200228,0.0003594925,0.0004033315,0.0003014659,0.0004072913,0.001132735,0.001240979,0.0006610438,0.003291626],"category_scores_gemma":[0.0006086334,0.0003592626,0.000420473,0.0002446255,0.000567591,0.0006975879,0.001009642,0.000486644,0.0007190717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004822138,"about_ca_system_score_gemma":0.0008679347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001484585,"about_ca_topic_score_gemma":0.001772621,"domain_scores_codex":[0.9994395,0.0001116027,0.00003763615,0.00009842279,0.0002239542,0.00008883265],"domain_scores_gemma":[0.999747,0.00003759168,0.00003562328,0.00005092663,0.00008722857,0.00004157906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001933521,0.0002782089,0.00304079,0.0005807935,0.00009150667,0.0004372689,0.0006831735,0.5813181,0.08714579,0.11928,0.002655426,0.2042956],"study_design_scores_gemma":[0.00007513209,0.0003264602,0.001469878,0.00006651688,0.00008827221,0.0002423832,0.0001934029,0.8865685,0.03238517,0.0106697,0.06787626,0.00003825602],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02255965,0.000163583,0.9584945,0.0001077975,0.00004739672,0.0002311852,0.00004139282,0.0008765924,0.01747789],"genre_scores_gemma":[0.477571,0.000267814,0.5126956,0.00007658909,0.00001705046,0.0004198123,0.0001206651,0.0001114524,0.008720026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003291626,"threshold_uncertainty_score":0.0110116,"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."}}