{"id":"W2914571830","doi":"10.1016/j.ecoser.2019.100897","title":"A dynamic eco-compensation standard for Hani Rice Terraces System in southwest China","year":2019,"lang":"en","type":"article","venue":"Ecosystem Services","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Guelph","keywords":"China; Geography; Compensation (psychology); Agroforestry; Environmental science; Archaeology","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":[0.001288938,0.0002610094,0.0002102897,0.001512329,0.001077733,0.000895285,0.000970428,0.0003816639,0.002042124],"category_scores_gemma":[0.001205876,0.000148386,0.0002282935,0.001482449,0.000386339,0.0008317687,0.0006998939,0.0002179811,0.0002146471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003734519,"about_ca_system_score_gemma":0.005108373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1679041,"about_ca_topic_score_gemma":0.2102777,"domain_scores_codex":[0.9990159,0.0001112569,0.0001145857,0.0001797853,0.0003927619,0.0001856792],"domain_scores_gemma":[0.9985899,0.00005233361,0.0001448374,0.0001517817,0.0009364878,0.0001245382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004586618,0.0003470776,0.6923134,0.0002296284,0.0001197937,0.0008658618,0.002101392,0.06939051,0.02493981,0.02097993,0.02159054,0.1666633],"study_design_scores_gemma":[0.00005955908,0.0001460653,0.8065265,0.00004954083,0.0000841084,0.0002467267,0.004553412,0.1498587,0.005242514,0.004679423,0.02846902,0.00008443525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693607,0.0001396611,0.0121707,0.0003270226,0.00003168912,0.00020103,0.002427046,0.0002978299,0.01504431],"genre_scores_gemma":[0.9894071,0.00003342047,0.005687288,0.00003579351,0.000005407733,0.00006956224,0.00194758,0.00001868047,0.002795047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1679041,"threshold_uncertainty_score":0.3338537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003531147463068936,"score_gpt":0.1983550092115936,"score_spread":0.1948238617485246,"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."}}