{"id":"W2056756002","doi":"10.5589/m03-037","title":"Methodologies for analyzing intrinsic and required DEM accuracy for hydrological applications of flash floods","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital elevation model; Flash flood; Computer science; Data mining; Scale (ratio); Iterative and incremental development; Remote sensing; Geography; Cartography; Flood myth","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":[0.0131807,0.001107557,0.0007577622,0.004062193,0.0004446162,0.002121396,0.001342419,0.0009952608,0.0009863959],"category_scores_gemma":[0.04579673,0.0005559283,0.0007390361,0.002492929,0.0006920337,0.001605888,0.001318413,0.0006848971,0.0003037746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008906137,"about_ca_system_score_gemma":0.00119263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001158937,"about_ca_topic_score_gemma":0.001580002,"domain_scores_codex":[0.9896548,0.00371592,0.001252013,0.0007497487,0.004374958,0.0002526432],"domain_scores_gemma":[0.9691536,0.01369591,0.003616841,0.003116078,0.01022103,0.0001964953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004568619,0.0003265618,0.03933657,0.002123171,0.0006042967,0.0004135126,0.001150066,0.1961741,0.06954932,0.03349113,0.001781503,0.6545929],"study_design_scores_gemma":[0.00008879612,0.0006325013,0.03957036,0.0005900474,0.0003980707,0.0008119417,0.0007277092,0.8059807,0.121989,0.01793316,0.01102371,0.0002540002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03037912,0.000424445,0.9670298,0.00006134095,0.00002134558,0.0002273165,0.0003486076,0.0004255332,0.001082585],"genre_scores_gemma":[0.1930471,0.0004497432,0.8049883,0.00002789116,0.00002817542,0.0004137524,0.0006334434,0.0001275437,0.0002839938],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0131807,"threshold_uncertainty_score":0.06970704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0460193375309562,"score_gpt":0.3076067086561282,"score_spread":0.2615873711251719,"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."}}