{"id":"W4411922867","doi":"10.1016/j.cacint.2025.100221","title":"Urban morphology impacts on urban microclimate using artificial intelligence – a review","year":2025,"lang":"en","type":"review","venue":"City and Environment Interactions","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; National Research Council Canada","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Microclimate; Urban morphology; Morphology (biology); Environmental science; Geography; Ecology; Environmental resource management; Architectural engineering; Environmental planning; Engineering; Urban planning; Biology; Zoology","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":[0.0006544187,0.001174974,0.001146536,0.002290332,0.00030179,0.0020433,0.0009382841,0.001011632,0.002392712],"category_scores_gemma":[0.001716746,0.0003590902,0.001337881,0.002374819,0.0004363912,0.001596338,0.0006362133,0.0007423335,0.0007596604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004702525,"about_ca_system_score_gemma":0.001076962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003569361,"about_ca_topic_score_gemma":0.002897722,"domain_scores_codex":[0.9997332,0.00005425541,0.00004212316,0.00007171693,0.00008082568,0.00001804065],"domain_scores_gemma":[0.9989618,0.000747323,0.0000967576,0.00002258808,0.0001477323,0.00002369526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000627478,0.000137157,0.004216438,0.04337391,0.000406087,0.0002159717,0.0002924193,0.006224453,0.00129107,0.00694182,0.01756427,0.9192736],"study_design_scores_gemma":[0.00001504815,0.0003587941,0.02402391,0.03212741,0.001953707,0.00185782,0.0007994563,0.007929448,0.002287346,0.01379871,0.9146158,0.0002326026],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001903282,0.992686,0.001811439,0.0006136175,0.00024927,0.0000197053,0.0001378017,0.00004438944,0.002534423],"genre_scores_gemma":[0.009345352,0.9887185,0.001091394,0.0001479137,0.0002252914,0.00001955308,0.0001165713,0.00001002883,0.0003254248],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003569361,"threshold_uncertainty_score":0.008004427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08322987954135247,"score_gpt":0.3383855484029293,"score_spread":0.2551556688615768,"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."}}