{"id":"W2980255429","doi":"10.1080/26395916.2019.1669713","title":"Disentangling ‘ecosystem services’ and ‘nature’s contributions to people’","year":2019,"lang":"en","type":"article","venue":"Ecosystems and People","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":281,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Framing (construction); Ecosystem services; Conceptual framework; Perspective (graphical); Valuation (finance); Sociology; Indigenous; Confusion; Epistemology; Political science; Social science; Psychology; Business; Ecosystem; Ecology; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003434438,0.0002112157,0.000384553,0.0000477227,0.0002381019,0.0001657617,0.00017904,0.0001599694,0.0008493992],"category_scores_gemma":[0.000006576429,0.0001685575,0.00004678693,0.0002590767,0.000002920321,0.0003080813,0.0002708527,0.0001367038,0.001592862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008138947,"about_ca_system_score_gemma":0.000007288129,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002479039,"about_ca_topic_score_gemma":0.1696003,"domain_scores_codex":[0.998528,0.00005808088,0.0003038725,0.0004936151,0.0002267255,0.0003897065],"domain_scores_gemma":[0.9991727,0.00007668269,0.00009671829,0.0003198934,0.00001939827,0.0003145728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001580954,0.00002219885,0.9968808,0.0003660976,0.00002497862,0.00000264604,0.001376178,0.0001188286,0.0004134348,0.0002400247,0.000399825,0.0001391817],"study_design_scores_gemma":[0.002208363,0.0003075107,0.7501459,0.0006151888,0.0001108016,0.0002390078,0.003600104,0.06917719,0.0005330651,0.0002751117,0.1715142,0.001273531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994692,0.0004318904,0.00001558471,0.0005496173,0.0007059104,0.0006854621,0.000231465,0.00006835948,0.002619699],"genre_scores_gemma":[0.99921,0.00005517492,0.00002891772,0.0002533797,0.0001574577,0.00004752751,0.00003632059,0.00002035087,0.0001908729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2467349,"threshold_uncertainty_score":0.9991845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002334938592413057,"score_gpt":0.2028091271542365,"score_spread":0.2004741885618234,"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."}}