{"id":"W4391026310","doi":"10.1007/s11069-023-06377-0","title":"Transferability of predictive models to map susceptibility of ephemeral gullies at large scale","year":2024,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Food and Agriculture","keywords":"Ephemeral key; Scale (ratio); Digital elevation model; Gully erosion; Transferability; Sensitivity (control systems); Cartography; Calibration; Remote sensing; Hydrology (agriculture); Geology; Erosion; Computer science; Geography; Machine learning; Geomorphology; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001144854,0.0005092111,0.0003191373,0.0004840282,0.0002334375,0.0006387767,0.0004746,0.0005285967,0.001115219],"category_scores_gemma":[0.005858914,0.000241984,0.0004529289,0.0003562304,0.0003239108,0.0009176172,0.0006914071,0.0006029245,0.0002290144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004412504,"about_ca_system_score_gemma":0.0005889853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01427434,"about_ca_topic_score_gemma":0.006335816,"domain_scores_codex":[0.999804,0.00006367674,0.000008998388,0.00006058301,0.00002964803,0.00003321959],"domain_scores_gemma":[0.9982271,0.001138584,0.0001574369,0.0002897144,0.0001363067,0.00005097462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001008345,0.00006803388,0.01538545,0.00002138173,0.00007438252,0.00005169899,0.0000463558,0.9588883,0.002968158,0.000727769,0.0002714727,0.0213962],"study_design_scores_gemma":[0.000004106204,0.00001788146,0.003955831,0.000001985312,0.000006089242,0.000008185434,0.00001201887,0.9945964,0.0004555144,0.0008856027,0.00005233696,0.000004070733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8701715,0.000104247,0.1249799,0.0002990226,0.00003431433,0.00003773565,0.0005012983,0.00138366,0.002488329],"genre_scores_gemma":[0.9962838,0.00001985121,0.003225188,0.00001571278,0.000005324309,0.00001015575,0.000173327,0.00002516826,0.0002414075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01427434,"threshold_uncertainty_score":0.02838248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01618840476415194,"score_gpt":0.2399428442830666,"score_spread":0.2237544395189147,"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."}}