{"id":"W1980304384","doi":"10.1080/19475705.2012.746243","title":"Integration of multicriteria evaluation and cellular automata methods for landslide simulation modelling","year":2013,"lang":"en","type":"article","venue":"Geomatics Natural Hazards and Risk","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Shanghai Ocean University","keywords":"Landslide; Cellular automaton; Digital elevation model; Computer science; Geographic information system; Elevation (ballistics); Flooding (psychology); Geology; Natural hazard; Representation (politics); Stream power; Civil engineering; Data mining; Geotechnical engineering; Remote sensing; Meteorology; Geography; Geomorphology; Algorithm; Engineering; Erosion; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008301465,0.0001210436,0.0001750479,0.00003711075,0.0001444347,0.00005313077,0.00005608288,0.0001138699,0.0000868004],"category_scores_gemma":[0.0001276816,0.00007930666,0.00004238141,0.00007646602,0.00006670538,0.0002440133,0.00005977726,0.0001027234,0.000004202353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003014955,"about_ca_system_score_gemma":0.000006888458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004230982,"about_ca_topic_score_gemma":0.00001347355,"domain_scores_codex":[0.999097,0.0001048374,0.0002889811,0.0001900978,0.0001753896,0.0001437066],"domain_scores_gemma":[0.9993731,0.0002125702,0.0001662877,0.0001298467,0.00006466194,0.00005355879],"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":[0.00002570521,0.00002610861,0.0009159239,0.0000512439,0.00003573603,9.70935e-8,0.001076525,0.1330239,0.02117489,0.00005553509,0.00006252714,0.8435518],"study_design_scores_gemma":[0.000622827,0.00005632674,0.003436165,0.00003117513,0.0001284677,0.000001374902,0.00009983609,0.9855585,0.002654916,0.007033592,0.000258051,0.0001187491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6870566,0.0004171241,0.3117864,0.00003514147,0.0001103678,0.0005022805,0.000009078302,0.00001584568,0.00006709166],"genre_scores_gemma":[0.7601216,0.0002280305,0.2395042,0.000008769715,0.00001992301,0.00001922606,0.00003335721,0.000008369889,0.0000564753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8525346,"threshold_uncertainty_score":0.3234032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729894047191562,"score_gpt":0.3136569347945175,"score_spread":0.2963579943226019,"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."}}