{"id":"W4280515457","doi":"10.3389/fbuil.2022.856873","title":"Development of a Cognitive Digital Twin for Building Management and Operations","year":2022,"lang":"en","type":"article","venue":"Frontiers in Built Environment","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Fuseforward (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Scalability; Cloud computing; Data access; Building automation; Ontology; Upload; Database; World Wide Web; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001342221,0.0005524324,0.0003151213,0.0009755567,0.0006114746,0.002625126,0.002003415,0.0008594389,0.005165456],"category_scores_gemma":[0.003237114,0.00044445,0.0005721675,0.0007906043,0.001131164,0.004573048,0.004770731,0.00163558,0.001791075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114053,"about_ca_system_score_gemma":0.003358003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004744387,"about_ca_topic_score_gemma":0.004708448,"domain_scores_codex":[0.998933,0.0001387824,0.00007304223,0.0001713422,0.000556457,0.0001274396],"domain_scores_gemma":[0.9986172,0.0001377675,0.00005981422,0.0004038179,0.0004577304,0.0003237958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003680587,0.0006310873,0.007933962,0.000579021,0.0001089628,0.001176474,0.004860798,0.03873625,0.09521819,0.2483432,0.0110498,0.5909942],"study_design_scores_gemma":[0.0001258503,0.001270774,0.005624923,0.0004706424,0.0001810157,0.002795476,0.002917238,0.3178623,0.1156926,0.05574881,0.4970959,0.0002144219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05063064,0.0001041972,0.919837,0.0004530718,0.0001146453,0.0003377251,0.0002182795,0.003185031,0.02511938],"genre_scores_gemma":[0.1850771,0.0001639929,0.8044038,0.0001368577,0.00001872124,0.0001671733,0.0004842292,0.0003425445,0.009205491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005165456,"threshold_uncertainty_score":0.01728016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01149874553727782,"score_gpt":0.2010721103461058,"score_spread":0.189573364808828,"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."}}