{"id":"W2980239312","doi":"10.1126/science.aaw3372","title":"Global modeling of nature’s contributions to people","year":2019,"lang":"en","type":"article","venue":"Science","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":459,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada); McGill University","funders":"Marcus och Amalia Wallenbergs minnesfond; Deutsche Forschungsgemeinschaft","keywords":"Pace; Climate change; Natural resource economics; Sustainable development; Face (sociological concept); Pollination; Development economics; Environmental planning; Scale (ratio); Environmental resource management; Geography; Global warming; Environmental protection; Ecology; Environmental science; Economics; Biology; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003449092,0.0005715262,0.0003206184,0.0005430453,0.0005463715,0.00123476,0.0009775516,0.001507609,0.007608968],"category_scores_gemma":[0.001555433,0.0003088188,0.000852613,0.001151195,0.0007627935,0.001749277,0.001247349,0.0008460247,0.0006790222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001827367,"about_ca_system_score_gemma":0.001156015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06943215,"about_ca_topic_score_gemma":0.03488699,"domain_scores_codex":[0.9998353,0.00005564156,0.000005083187,0.00004943533,0.00002608096,0.00002842741],"domain_scores_gemma":[0.9996674,0.0001274077,0.00003975461,0.00003835844,0.00007243219,0.00005463304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001518421,0.00001884242,0.004861494,0.00002555218,0.00003989206,0.00005738778,0.0001095359,0.9436246,0.0002350856,0.04034119,0.005539756,0.005131488],"study_design_scores_gemma":[0.0000314958,0.00002508781,0.004925859,0.00002859739,0.00004133914,0.00005189216,0.0002430598,0.9117457,0.0001058756,0.0582419,0.02452232,0.00003690592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4271736,0.001946991,0.1948179,0.02085703,0.0009437277,0.000131514,0.01696291,0.001218073,0.3359482],"genre_scores_gemma":[0.9568577,0.001308192,0.01367616,0.0007383435,0.0001253383,0.000182246,0.002593156,0.0002364711,0.02428246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06943215,"threshold_uncertainty_score":0.138056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003695374351549715,"score_gpt":0.2441086555175574,"score_spread":0.2404132811660077,"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."}}