{"id":"W1986344304","doi":"10.5539/jgg.v5n3p101","title":"Post Seismic Debris Flow Modelling Using Flo-2D; Case Study of Yingxiu, Sichuan Pronvince, China","year":2013,"lang":"en","type":"article","venue":"Journal of Geography and Geology","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chengdu University; Chengdu University of Technology","keywords":"Debris flow; Debris; Geology; Landslide; Hydrology (agriculture); Channel (broadcasting); Flow (mathematics); Entrainment (biomusicology); Magnitude (astronomy); Mass wasting; Sediment; Drainage basin; Geomorphology; Environmental science; Geotechnical engineering; Geography","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":[0.0003854427,0.000756003,0.0004713909,0.001021661,0.0007317216,0.001064118,0.001308386,0.00111369,0.001008169],"category_scores_gemma":[0.0006067551,0.0003838864,0.0007032814,0.0007436873,0.0005638618,0.0004391134,0.0005961393,0.0004056832,0.00008545237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001496036,"about_ca_system_score_gemma":0.0012862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1638084,"about_ca_topic_score_gemma":0.08883112,"domain_scores_codex":[0.9998838,0.00002175433,0.00001010235,0.00002734713,0.00002289104,0.00003409832],"domain_scores_gemma":[0.9997293,0.0001166754,0.0000345653,0.00002135755,0.00006117974,0.00003689869],"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":[0.00004476443,0.00008128991,0.01635256,0.00003080672,0.00002067161,0.0006026608,0.0001079312,0.978791,0.0006843114,0.0003784744,0.0002073717,0.002698133],"study_design_scores_gemma":[0.000008708106,0.00001881421,0.003791938,0.000004381973,0.000006710319,0.00002160898,0.00006427641,0.9956012,0.0002336546,0.00007194575,0.0001705833,0.00000623918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941974,0.00009587918,0.003408813,0.00007008405,0.000009935465,0.00003407685,0.0003394431,0.0001082786,0.001736116],"genre_scores_gemma":[0.9973138,0.00006418736,0.001685323,0.000007139612,0.000003465848,0.00002252686,0.0002229738,0.000008847829,0.0006717581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1638084,"threshold_uncertainty_score":0.3257098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006800052381955572,"score_gpt":0.2080196288163861,"score_spread":0.2012195764344306,"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."}}