{"id":"W4323315261","doi":"10.1080/23744731.2023.2187611","title":"A simulation-based approach for evaluating indoor environmental quality at the early design stage","year":2023,"lang":"en","type":"article","venue":"Science and Technology for the Built Environment","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Facade; Workflow; Thermal comfort; Computer science; Post-occupancy evaluation; Parametric design; Set (abstract data type); Parametric statistics; Environmental quality; Architectural engineering; Simulation; Engineering; Civil 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001701205,0.001293731,0.0008650231,0.001666279,0.0005196032,0.001540054,0.001245888,0.0009647456,0.003566524],"category_scores_gemma":[0.002767957,0.0005735844,0.001294956,0.001160501,0.0005370411,0.000809779,0.0011756,0.0007591712,0.0004295335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357989,"about_ca_system_score_gemma":0.001646847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007994708,"about_ca_topic_score_gemma":0.009303154,"domain_scores_codex":[0.9990798,0.0004157575,0.00005441971,0.00008818242,0.000299492,0.0000623095],"domain_scores_gemma":[0.9988092,0.0006172586,0.0001286146,0.0001617536,0.0002333685,0.0000498532],"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":[0.00004341004,0.00008745844,0.001412136,0.00008897339,0.00004167595,0.00003653136,0.00008326748,0.9732218,0.002919069,0.006591662,0.0002515448,0.01522254],"study_design_scores_gemma":[0.000007793211,0.00005352889,0.0002739058,0.0000149614,0.00001475661,0.00001288356,0.00003236039,0.9952924,0.001162404,0.002006788,0.001116202,0.00001194655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02835931,0.0001500224,0.9616985,0.00008858152,0.00002820044,0.0002976469,0.0002920503,0.0007209461,0.008364708],"genre_scores_gemma":[0.5796021,0.0004248549,0.41604,0.00004811356,0.00001496409,0.0009373739,0.00058441,0.0001167815,0.002231322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007994708,"threshold_uncertainty_score":0.01589638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05330777493840046,"score_gpt":0.2879790163347112,"score_spread":0.2346712413963108,"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."}}