{"id":"W2429610540","doi":"10.1126/science.aaf2295","title":"Improvements in ecosystem services from investments in natural capital","year":2016,"lang":"en","type":"article","venue":"Science","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":1689,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"EUROPEAN Fisheries Control Agency; Ministère des Forêts, de la Faune et des Parcs","keywords":"Ecosystem services; Natural capital; Ecosystem; Biodiversity; Business; Habitat; Environmental resource management; Ecosystem management; Ecosystem health; China; Flood myth; Carbon sequestration; Ecosystem valuation; Environmental science; Natural resource economics; Ecology; Geography; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0004993672,0.0004474677,0.0001444002,0.0007700444,0.0004039316,0.00095026,0.0002531658,0.0003106576,0.004315684],"category_scores_gemma":[0.001148466,0.000082433,0.0003005264,0.0009495197,0.0003674035,0.0009437514,0.001299203,0.0004486978,0.0003871339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002104957,"about_ca_system_score_gemma":0.002866908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180084,"about_ca_topic_score_gemma":0.0467636,"domain_scores_codex":[0.9997327,0.00003114852,0.00001104129,0.00002645957,0.00006554543,0.0001330201],"domain_scores_gemma":[0.9994165,0.00002671126,0.0001227287,0.00004439978,0.0001554656,0.0002341969],"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":[0.0003445983,0.0003776747,0.4337434,0.0006763141,0.0004387886,0.001748458,0.0008597447,0.01480506,0.0131253,0.04529924,0.02033094,0.4682506],"study_design_scores_gemma":[0.00005168032,0.0002150779,0.894619,0.0002116613,0.0002274936,0.0004756351,0.000766655,0.005750437,0.004183297,0.01188204,0.08158157,0.00003551584],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.901473,0.003981685,0.004188845,0.004236424,0.0001684066,0.0001038537,0.002155297,0.0003091384,0.08338331],"genre_scores_gemma":[0.9914465,0.001339616,0.0008851036,0.0002466041,0.00003512568,0.00001914484,0.0006901041,0.00000992371,0.00532791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01180084,"threshold_uncertainty_score":0.02346432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004237735465020013,"score_gpt":0.1976412273329147,"score_spread":0.1934034918678947,"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."}}