{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003845858,0.00006932877,0.0001255528,0.00001260937,0.00004261347,0.00001762055,0.00009334714,0.00005083321,0.0002683504],"category_scores_gemma":[0.00005716218,0.0000551639,0.00001585689,0.0000747082,0.00002383916,0.0001516636,0.0000837208,0.0000603051,0.00001932336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004594732,"about_ca_system_score_gemma":0.000005722729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009837699,"about_ca_topic_score_gemma":0.001472746,"domain_scores_codex":[0.9992962,0.00004785672,0.0001982976,0.0001706719,0.0001709493,0.0001159677],"domain_scores_gemma":[0.9997374,0.00003593737,0.00008119809,0.00009673737,0.000007539115,0.00004121099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000142109,0.00004005929,0.9959299,0.00003940259,0.000001992035,3.330231e-7,0.0001023711,0.00002805411,0.0003179954,0.00007074018,0.00003253661,0.003422398],"study_design_scores_gemma":[0.0002545606,0.00002505743,0.9861029,0.0000174469,0.000002574906,0.000001105574,0.000006086895,0.01130261,0.000284633,0.001309997,0.0006246114,0.00006844931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975049,0.000006344878,0.0004002716,0.0000697494,0.0000774548,0.00007618514,0.00005218096,0.000007895119,0.001805038],"genre_scores_gemma":[0.9997955,0.000009241832,0.00002249918,0.00002067317,0.00005271173,0.000004830568,0.00008472794,0.000003256963,0.000006557078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01127456,"threshold_uncertainty_score":0.2938249,"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."}}