{"id":"W4400766989","doi":"10.1016/j.buildenv.2024.111857","title":"Considering diverse occupant profiles in building design decisions","year":2024,"lang":"en","type":"article","venue":"Building and Environment","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Workflow; Architectural engineering; Built environment; Computer science; Process (computing); Building design; Parametric design; Design process; Occupancy; Range (aeronautics); Engineering; Systems engineering; Parametric statistics; Construction engineering; Civil engineering; Operations management; Work in process","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":[0.009838051,0.001328781,0.0008241475,0.00196634,0.00129471,0.003402841,0.0008431918,0.001036821,0.002344905],"category_scores_gemma":[0.01349913,0.0007156999,0.001048926,0.001078682,0.0006365039,0.002535067,0.001937439,0.0008156166,0.000542897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418218,"about_ca_system_score_gemma":0.002557311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002996203,"about_ca_topic_score_gemma":0.00915561,"domain_scores_codex":[0.9945057,0.003320845,0.000306485,0.0003561928,0.001039333,0.0004713946],"domain_scores_gemma":[0.9944437,0.003223137,0.0005778394,0.0005766795,0.0008750106,0.000303653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007652688,0.000875456,0.06682546,0.0006851064,0.0001616602,0.0008651341,0.008978226,0.4707872,0.02758405,0.01695127,0.001868283,0.403653],"study_design_scores_gemma":[0.0001254324,0.002254968,0.05538197,0.000821074,0.0003318173,0.0009387982,0.02664965,0.7999353,0.02855641,0.05463829,0.02995932,0.000406949],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5795086,0.0005446905,0.4007088,0.0006414975,0.0000338783,0.001044538,0.0002017928,0.0004202412,0.01689607],"genre_scores_gemma":[0.7735975,0.0003002891,0.2245053,0.00005845191,0.000007964548,0.0002662008,0.000177227,0.00004937066,0.001037695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009838051,"threshold_uncertainty_score":0.05202919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02525624801655163,"score_gpt":0.2186183701160772,"score_spread":0.1933621220995256,"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."}}