{"id":"W2784827842","doi":"10.5539/enrr.v10n1p28","title":"Urban Erosion Potential Risk Mapping with GIS","year":2020,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Stormwater; Erosion; Environmental science; Surface runoff; Geospatial analysis; Hydrology (agriculture); Geographic information system; Land use; Land cover; Erosion control; Water resource management; Computer science; Civil engineering; Remote sensing; Geography; Geology; Engineering; 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":[0.0002804713,0.0004697067,0.0002120098,0.001906331,0.0002188624,0.0008912635,0.0004475984,0.000177757,0.006306767],"category_scores_gemma":[0.0007421626,0.0002296956,0.0003605458,0.001842857,0.0001188609,0.0004694253,0.0006859557,0.0001683077,0.0009076768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003781783,"about_ca_system_score_gemma":0.0004534582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007936515,"about_ca_topic_score_gemma":0.008612913,"domain_scores_codex":[0.9998511,0.00003341577,0.0000114902,0.0000330957,0.00005658426,0.00001424726],"domain_scores_gemma":[0.9998343,0.00005954157,0.00001868375,0.00002733462,0.00005123775,0.00000887294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001710234,0.0002099361,0.02758814,0.0002182067,0.0001024994,0.0004067117,0.0006217842,0.5488945,0.006793275,0.01742589,0.01712053,0.3804475],"study_design_scores_gemma":[0.00002843259,0.00004275436,0.01238069,0.00003700275,0.00002280517,0.0001632322,0.0004156732,0.9410622,0.005118635,0.009332429,0.03135911,0.00003701217],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2092941,0.0001580533,0.7191279,0.000235428,0.00003095896,0.0005879801,0.01590766,0.01653272,0.03812532],"genre_scores_gemma":[0.5728365,0.0001621057,0.4153048,0.00001945221,0.000009964148,0.0003678396,0.005763153,0.0002877458,0.005248532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007936515,"threshold_uncertainty_score":0.02109826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0301424869120178,"score_gpt":0.2252258360654288,"score_spread":0.195083349153411,"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."}}