{"id":"W4286715683","doi":"10.1080/10106049.2022.2105407","title":"Furthering the precision of RUSLE soil erosion with PSInSAR data: an innovative model","year":2022,"lang":"en","type":"article","venue":"Geocarto International","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Universal Soil Loss Equation; Environmental science; Erosion; Hydrology (agriculture); WEPP; Soil science; Remote sensing; Soil loss; Geology; Soil conservation; Geography; Geomorphology; Geotechnical engineering","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":[0.0002969403,0.00006889491,0.00007013731,0.00001151482,0.0001764585,0.00002184584,0.0006437717,0.00001672342,0.00059968],"category_scores_gemma":[0.000009247329,0.00002309715,0.00001767816,0.0002608641,0.00004045054,0.0002003746,0.0002023335,0.0001079698,0.000002801134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001712649,"about_ca_system_score_gemma":0.0000161342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002130061,"about_ca_topic_score_gemma":0.0003775897,"domain_scores_codex":[0.9990097,0.0000348263,0.0001509884,0.0002160225,0.0004967767,0.00009171593],"domain_scores_gemma":[0.9996213,0.00004316025,0.00007864718,0.0001073564,0.0001265644,0.00002302217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001342111,0.001324548,0.08368382,0.000006011024,0.0001211082,0.00001160681,0.004619034,0.07711191,0.6769965,0.00728335,0.00307945,0.1444205],"study_design_scores_gemma":[0.001680039,0.001961946,0.4055924,0.00006275846,0.00003980413,0.00004013878,0.005857022,0.4731768,0.0180351,0.002143021,0.09074518,0.0006656959],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972317,0.00001181146,0.0001410279,0.001169929,0.0001639491,0.0000956768,0.0002824354,0.00002309058,0.0008804441],"genre_scores_gemma":[0.9983221,0.000006186752,0.0001498076,0.0003144635,0.0000666751,0.0000172591,0.0008271407,9.100269e-7,0.0002954171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6589615,"threshold_uncertainty_score":0.6566075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05248421633051384,"score_gpt":0.2544389446755594,"score_spread":0.2019547283450456,"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."}}