{"id":"W2387494871","doi":"","title":"Spatial distribution characteristics and accessibility of national wetland parks in China","year":2014,"lang":"en","type":"article","venue":"Shengtaixue zazhi","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Geography; China; Wetland; Distribution (mathematics); National park; Spatial distribution; Physical geography; Range (aeronautics); Cartography; Forestry; Remote sensing; Ecology; Archaeology","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":[0.0002852189,0.0001085128,0.0001200717,0.001338872,0.0002328568,0.0002540016,0.0002077563,0.0000668321,0.001003066],"category_scores_gemma":[0.0007737855,0.00008844661,0.0002048349,0.001933248,0.0001973893,0.0002902189,0.000363695,0.00006351831,0.00006967282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005464064,"about_ca_system_score_gemma":0.0005633557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03484147,"about_ca_topic_score_gemma":0.05579644,"domain_scores_codex":[0.9997919,0.00002840068,0.00002490393,0.00005415108,0.00006015343,0.00004046082],"domain_scores_gemma":[0.9995741,0.00007122775,0.000134555,0.00003265545,0.0001272594,0.00006020466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004468116,0.00001562665,0.973466,0.00006298519,0.00004632448,0.000256855,0.0007533844,0.002028898,0.001136145,0.0006089206,0.0003841304,0.021196],"study_design_scores_gemma":[0.000001632244,0.00001010171,0.9974992,0.000003576111,0.000006304141,0.00008388536,0.0001990973,0.001534848,0.00006886259,0.00009654197,0.0004919294,0.000004032319],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986319,0.00006436469,0.00025929,0.00001508868,8.484391e-7,0.000005025237,0.000324762,0.000007238597,0.0006915595],"genre_scores_gemma":[0.9991235,0.00003888752,0.0002336705,0.000001912414,0.00000107135,0.000006916036,0.0003275649,9.324139e-7,0.0002656238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03484147,"threshold_uncertainty_score":0.06927735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005214008232540147,"score_gpt":0.2151052248676599,"score_spread":0.2098912166351197,"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."}}