{"id":"W3006066493","doi":"10.3390/su12041360","title":"Evidence-Based Landscape Architecture for Human Health and Well-Being","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Yard; Landscape design; Architecture; Landscape architecture; Architectural engineering; Environmental planning; Urban design; Human health; Natural landscape; Built environment; Environmental resource management; Geography; Natural (archaeology); Civil engineering; Engineering; Environmental science; Environmental health; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004947714,0.0001189783,0.0001851979,0.00001630566,0.0003295425,0.00002647805,0.0001289142,0.00004645234,0.0002676743],"category_scores_gemma":[0.0003605684,0.0001042215,0.00005208924,0.0001575962,0.0001546461,0.0001061529,0.0000946124,0.0001473634,0.000009286186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003370406,"about_ca_system_score_gemma":0.000191204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079512,"about_ca_topic_score_gemma":0.001185905,"domain_scores_codex":[0.9987465,0.00009988566,0.000178699,0.000420943,0.0001617122,0.0003922306],"domain_scores_gemma":[0.9991661,0.0001365848,0.00006607612,0.0002102738,0.00002415523,0.0003968397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001001561,0.0000292569,0.9818661,0.0005887401,0.000002108803,0.000001665738,0.003207492,0.0002409595,0.00002874451,0.0004229631,0.005327531,0.008184339],"study_design_scores_gemma":[0.002128173,0.004116341,0.8222135,0.0001211195,0.0000285177,0.000002731277,0.004263376,0.004794859,0.0001415458,0.06819752,0.09325496,0.0007374181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8569412,0.0003483114,0.005479048,0.1356226,0.00001775218,0.001218466,0.000003052257,0.000077094,0.0002925885],"genre_scores_gemma":[0.9909146,0.00001013011,0.0008943669,0.007948031,0.00006806119,0.00003720424,0.000005559437,0.00001104163,0.0001109959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1596526,"threshold_uncertainty_score":0.4250031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02433695440243444,"score_gpt":0.2921194719488669,"score_spread":0.2677825175464325,"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."}}