{"id":"W3138762857","doi":"10.5751/es-12204-260128","title":"What do people value in urban green? Linking characteristics of urban green spaces to users&amp;#8217; perceptions of nature benefits, disturbances, and disservices","year":2021,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Urban green space; Perception; Geography; Socioeconomics; Environmental planning; Business; Sociology; Psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001467738,0.0001790244,0.0002323321,0.0009412532,0.0005843608,0.002604509,0.0001990191,0.0008415426,0.00285363],"category_scores_gemma":[0.005854652,0.0002002249,0.0003547753,0.0009912759,0.002359911,0.002077134,0.001146482,0.0008194135,0.0003559398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006679737,"about_ca_system_score_gemma":0.0002868951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005133636,"about_ca_topic_score_gemma":0.01349734,"domain_scores_codex":[0.999198,0.0003776173,0.00004484344,0.00004797039,0.0002231123,0.0001085441],"domain_scores_gemma":[0.9951445,0.002002092,0.001414241,0.0001965193,0.0004846263,0.0007580206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002051124,0.0001838763,0.8940298,0.0001385059,0.0002601493,0.0001960985,0.0542323,0.0003687899,0.0008901531,0.003305715,0.002447848,0.04374165],"study_design_scores_gemma":[0.00002542875,0.000213296,0.8296538,0.0001352091,0.00009597177,0.0002702769,0.1552898,0.0007038645,0.0003830606,0.006525738,0.00663747,0.00006612601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908885,0.0005851445,0.0002622456,0.002028247,0.0000195622,0.000007539204,0.00011562,0.000003391513,0.00608976],"genre_scores_gemma":[0.9991965,0.0002653303,0.0001173206,0.0001730343,0.000006412734,0.000003310523,0.00003588729,0.000001768745,0.0002004846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005133636,"threshold_uncertainty_score":0.01020747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007647377944735553,"score_gpt":0.2429071154258654,"score_spread":0.2352597374811299,"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."}}