{"id":"W2285313264","doi":"10.1016/j.jglr.2015.12.012","title":"Erosion and deposition within Poyang Lake: evidence from a decade of satellite data","year":2016,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China","keywords":"Wetland; Environmental science; Hydrology (agriculture); Elevation (ballistics); Bathymetry; Physical geography; Erosion; Water quality; Water level; Oceanography; Geology; Geography; Ecology; Geomorphology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0007281583,0.0001995403,0.0002729495,0.001255044,0.0004254782,0.0008309548,0.0003955396,0.0004790277,0.0005605144],"category_scores_gemma":[0.002564047,0.0002758527,0.0002798132,0.004494399,0.0006129169,0.001577075,0.001136195,0.0002899595,0.0001158188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005188225,"about_ca_system_score_gemma":0.0008566517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06623199,"about_ca_topic_score_gemma":0.16089,"domain_scores_codex":[0.9996076,0.00007766545,0.00007931639,0.00008134527,0.0001047951,0.00004930562],"domain_scores_gemma":[0.9974016,0.00060061,0.001157142,0.0002700383,0.0004207787,0.000149856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009044239,0.00002732899,0.9906176,0.00005621033,0.0001180631,0.0001866133,0.001150668,0.0002497121,0.0005446004,0.00006104472,0.000245305,0.00665253],"study_design_scores_gemma":[0.000003443638,0.00001251319,0.9985832,0.000009885839,0.00002714581,0.00003933454,0.0005431739,0.0002896931,0.00007664014,0.00001838006,0.0003924875,0.000004054213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984941,0.0001558911,0.00005763198,0.00006128677,0.000002459641,0.000002962692,0.0006517077,0.000003844182,0.0005699878],"genre_scores_gemma":[0.9979013,0.0003027457,0.0002124469,0.00002161023,0.00000813736,0.000009408156,0.001344303,0.000003543576,0.0001966903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06623199,"threshold_uncertainty_score":0.1316929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09881176529915213,"score_gpt":0.3714463967452586,"score_spread":0.2726346314461064,"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."}}