{"id":"W2603984089","doi":"10.5751/es-09168-220151","title":"Shifts in ecosystem services in deprived urban areas: understanding people&amp;#8217;s responses and consequences for well-being","year":2017,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Biodiversa+; Azim Premji University; United States Agency for International Development","keywords":"Ecosystem services; Ecosystem; Urban ecosystem; Ecology; Geography; Urbanization; Environmental resource management; Environmental science; Biology","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":[0.0007166922,0.000158996,0.0002958161,0.0008181098,0.0006462378,0.001344091,0.0003367498,0.0006883282,0.003447569],"category_scores_gemma":[0.002832159,0.0001830137,0.0003101906,0.0009304442,0.001575898,0.001587311,0.002146821,0.000838917,0.0002500949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322859,"about_ca_system_score_gemma":0.0007861752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03946454,"about_ca_topic_score_gemma":0.1055947,"domain_scores_codex":[0.9996632,0.0001057214,0.00001722056,0.00006031336,0.00005117034,0.000102286],"domain_scores_gemma":[0.999025,0.0002638114,0.0002624129,0.00005551488,0.0001156365,0.0002777036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00018764,0.0001924971,0.8880894,0.0002181935,0.0001610596,0.0003164477,0.03267463,0.000618536,0.0008732469,0.00292173,0.003520587,0.07022608],"study_design_scores_gemma":[0.000004790608,0.00006538802,0.9569867,0.0001111641,0.00002619191,0.0001162546,0.03559436,0.0005555003,0.0001120512,0.003960611,0.002445961,0.00002106053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923637,0.001229385,0.0001875105,0.003169577,0.00001731004,0.000007450325,0.0003488083,0.000003245142,0.002672977],"genre_scores_gemma":[0.998728,0.0007216334,0.0001071588,0.0001777839,0.00000670904,0.000009162931,0.0001080694,0.000001687095,0.0001397146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03946454,"threshold_uncertainty_score":0.07846963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02088335397586212,"score_gpt":0.2508141390628988,"score_spread":0.2299307850870367,"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."}}