{"id":"W143046059","doi":"","title":"VEGETATION'S IMPACT ON URBAN INFRASTRUCTURE","year":2006,"lang":"en","type":"article","venue":"","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Liability; Business; Happiness; Urban forestry; Urban forest; Green infrastructure; Asset (computer security); Value (mathematics); Environmental planning; Process (computing); Geography; Forestry; Finance; Political science; Computer science; Computer security","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":[0.000241596,0.0001514249,0.0001182592,0.0008316257,0.00167671,0.002323685,0.0004775952,0.0003702959,0.01522303],"category_scores_gemma":[0.001873014,0.00009173415,0.0002521504,0.001464267,0.001314654,0.0008427768,0.002285253,0.0004994167,0.0006413216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002988313,"about_ca_system_score_gemma":0.001266533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02523573,"about_ca_topic_score_gemma":0.08234814,"domain_scores_codex":[0.9992963,0.0002181825,0.00001478527,0.0000455165,0.0001368474,0.0002882883],"domain_scores_gemma":[0.9989905,0.0001771522,0.0002338799,0.00005212116,0.0002106465,0.0003356949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003945886,0.0002813521,0.5177822,0.0003919591,0.0001935409,0.003240977,0.008465166,0.00932031,0.003517136,0.1785788,0.02926136,0.2485727],"study_design_scores_gemma":[0.00002151975,0.0002935759,0.7886192,0.0003047954,0.00009237704,0.001375026,0.02063757,0.002459411,0.0008110336,0.01973522,0.1656037,0.00004647814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.726776,0.001995973,0.001259831,0.008469037,0.0001606219,0.00002733982,0.0009177522,0.00007811822,0.2603153],"genre_scores_gemma":[0.9964275,0.0003701495,0.0001753295,0.0001109318,0.00002430985,0.000004952495,0.0001014626,0.000008549575,0.002776842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02523573,"threshold_uncertainty_score":0.05092609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004743153845068758,"score_gpt":0.2328608178028302,"score_spread":0.2281176639577614,"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."}}