{"id":"W7078600459","doi":"","title":"WeDesign: Generative AI-Facilitated Community Consultations for Urban Public Space Design","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stakeholder; Generative grammar; Citizen journalism; Urban planning; Creativity; Public participation; Participatory GIS; Generative model; Facilitation; Generative Design","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004972816,0.0006314339,0.0002057585,0.0007324939,0.002213345,0.002351109,0.001919456,0.001000475,0.02396115],"category_scores_gemma":[0.008569302,0.0003229832,0.0003373792,0.0006492996,0.002192154,0.002314659,0.006418164,0.000951994,0.002150212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001560405,"about_ca_system_score_gemma":0.002036968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002557583,"about_ca_topic_score_gemma":0.007845211,"domain_scores_codex":[0.9972549,0.002052919,0.00004674756,0.0002215993,0.0002357785,0.0001881641],"domain_scores_gemma":[0.9931844,0.005229487,0.0001507477,0.0006202324,0.0002485423,0.0005667186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001933179,0.00147492,0.006487076,0.001981284,0.00006347603,0.002993737,0.1873289,0.01226794,0.04926688,0.08915097,0.05453726,0.5925144],"study_design_scores_gemma":[0.0009779149,0.001252539,0.00840312,0.0008753354,0.00006341477,0.001717356,0.08878949,0.0511368,0.02710087,0.06735834,0.7520608,0.0002640118],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3429649,0.0003900763,0.4309896,0.002852244,0.0003322652,0.003169014,0.001051297,0.007136713,0.2111139],"genre_scores_gemma":[0.7281712,0.0001936498,0.2344129,0.0002672434,0.0000382037,0.002289837,0.0005830651,0.0006253544,0.03341867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02396115,"threshold_uncertainty_score":0.08015805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048766585153788,"score_gpt":0.2943713404742883,"score_spread":0.1894946819589095,"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."}}