{"id":"W4414014551","doi":"10.3390/buildings15173212","title":"Generative AI for Architectural Façade Design: Measuring Perceptual Alignment Across Geographical, Objective, and Affective Descriptors","year":2025,"lang":"en","type":"article","venue":"Buildings","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Workplace Health, Safety and Compensation Commission","funders":"","keywords":"Perception; Generative grammar; Generative model; Generative Design; Computer science; Artificial intelligence; Pattern recognition (psychology); Engineering; Psychology; Metric (unit)","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":[0.001842107,0.0004711277,0.0001887447,0.001047065,0.0002948815,0.002052426,0.0004403703,0.0005005426,0.00301211],"category_scores_gemma":[0.02148075,0.000269992,0.0005303806,0.0005829128,0.001017507,0.001595307,0.001339971,0.0005854325,0.0005476534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008828608,"about_ca_system_score_gemma":0.0003225429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001516535,"about_ca_topic_score_gemma":0.001951874,"domain_scores_codex":[0.9990459,0.0003742788,0.00005018643,0.0001982938,0.0002830382,0.00004822516],"domain_scores_gemma":[0.9944988,0.003321693,0.0007496285,0.000714371,0.0005016382,0.0002139583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001892952,0.000610991,0.1475506,0.002003311,0.0005982586,0.00030715,0.02063699,0.1011544,0.1917186,0.036085,0.003726134,0.4937155],"study_design_scores_gemma":[0.00016947,0.001443585,0.3448052,0.0004181679,0.0004067382,0.001126129,0.009376992,0.5173319,0.04919904,0.06076616,0.01455927,0.0003973339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7737079,0.0004224448,0.1978361,0.0002216271,0.00006631558,0.000413946,0.0003739749,0.000779113,0.0261785],"genre_scores_gemma":[0.9571439,0.00009325698,0.04166028,0.00005488211,0.000006225334,0.0001128558,0.0002363375,0.00008196939,0.000610253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00301211,"threshold_uncertainty_score":0.01007652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04261359110220098,"score_gpt":0.3131460372711753,"score_spread":0.2705324461689743,"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."}}