{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003126257,0.0001272902,0.0001286875,0.00001770127,0.0005052977,0.00007888558,0.0001966657,0.00007338877,0.000560553],"category_scores_gemma":[0.00001941023,0.00004463942,0.00004748184,0.0002282406,0.0001987799,0.00008354485,0.0001142992,0.0004955982,0.00006845635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001665373,"about_ca_system_score_gemma":0.000001981181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001372056,"about_ca_topic_score_gemma":0.00001729863,"domain_scores_codex":[0.998208,0.0001466087,0.0001307602,0.0003952082,0.0007617043,0.0003576521],"domain_scores_gemma":[0.9995416,0.0001144758,0.00003530598,0.00004665627,0.00001289184,0.0002490435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007062832,0.00009420128,0.3171843,0.00001646982,0.00003144806,0.00005145698,0.001826609,0.00001955702,0.5890039,0.00001876115,0.003745927,0.08730106],"study_design_scores_gemma":[0.0003819922,0.0006488006,0.8190327,0.00001865895,0.000008407854,0.000002502768,0.001042034,0.0006687919,0.002034684,0.00001303508,0.1759684,0.0001799346],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949185,0.001126279,0.000004092518,0.00344244,0.00001826289,0.0002032418,0.00001167663,0.0000380317,0.0002375208],"genre_scores_gemma":[0.9977775,0.0009647144,0.00005610701,0.000202026,0.0002472732,0.000008782386,0.00003591296,0.000001685175,0.0007059608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5869692,"threshold_uncertainty_score":0.6137662,"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."}}