{"id":"W3033198486","doi":"10.3390/cli8060072","title":"Microclimate Analysis as a Design Driver of Architecture","year":2020,"lang":"en","type":"article","venue":"Climate","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Mitacs","keywords":"Microclimate; Architectural engineering; Thermal comfort; Interoperability; Architecture; Computer science; Context (archaeology); Architectural design; Scope (computer science); Systems engineering; Environmental science; Environmental resource management; Engineering; Meteorology; Geography; World Wide Web","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":[0.00174498,0.0007196448,0.0003451977,0.0007764513,0.000603613,0.003074827,0.000908134,0.0004938208,0.00331236],"category_scores_gemma":[0.002853255,0.0005123075,0.0005411823,0.0004517059,0.0009323131,0.001725471,0.001211064,0.000858908,0.0006867059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009876159,"about_ca_system_score_gemma":0.001328215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00315753,"about_ca_topic_score_gemma":0.006715854,"domain_scores_codex":[0.9989716,0.0003847286,0.0000369271,0.0001260857,0.000402958,0.00007772662],"domain_scores_gemma":[0.9985871,0.0005295768,0.0001336057,0.0002865414,0.0003617444,0.0001014186],"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":[0.000226193,0.0001693841,0.03088959,0.00105297,0.0002176673,0.0003810179,0.007992689,0.5322502,0.06521348,0.09352002,0.007802361,0.2602844],"study_design_scores_gemma":[0.00002929451,0.0002598169,0.02206385,0.0002354402,0.0001626857,0.0003874997,0.002103406,0.778927,0.03725202,0.04172651,0.1166568,0.000195665],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2042727,0.0006493905,0.7424521,0.001079967,0.0001093986,0.0001739944,0.0004746971,0.004151375,0.04663648],"genre_scores_gemma":[0.7809275,0.0004828564,0.2116794,0.000110899,0.00002818423,0.0001452531,0.0003055256,0.001227218,0.005093044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00331236,"threshold_uncertainty_score":0.01108092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440899936069007,"score_gpt":0.2167081535893682,"score_spread":0.2022991542286782,"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."}}