{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001906066,0.0001469868,0.0001220088,0.0001540053,0.00007549236,0.00007171421,0.00006450833,0.00007126953,0.00003685708],"category_scores_gemma":[0.00001262931,0.0001433327,0.00002842016,0.000102633,0.00003167683,0.0001343598,0.00006222718,0.0001417826,0.000005291557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009583994,"about_ca_system_score_gemma":0.000006794805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001225832,"about_ca_topic_score_gemma":8.458884e-7,"domain_scores_codex":[0.9992427,0.00001824557,0.0001726919,0.0002359079,0.0001083323,0.0002221631],"domain_scores_gemma":[0.9996811,0.0001280933,0.000009343134,0.0001192783,0.000001413724,0.0000607869],"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":[0.000003250917,0.000007993649,0.0003892903,0.00002284679,0.00001772133,0.00003905691,0.0001278424,0.9666372,0.005965236,0.002196621,0.0001844802,0.02440846],"study_design_scores_gemma":[0.0001757912,0.00002070153,0.0007325062,0.0003378983,0.00002086506,0.00003318622,0.00007225129,0.9805706,0.008865028,0.001595257,0.007300178,0.0002757067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4406509,0.002623071,0.5559593,0.00004581453,0.0002380113,0.0001079272,0.000002908714,0.0002578154,0.0001143133],"genre_scores_gemma":[0.928584,0.002073314,0.06918909,0.00001479245,0.00004036118,0.00003360924,0.000002278284,0.00002905137,0.00003354178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4879331,"threshold_uncertainty_score":0.5844939,"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."}}