{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007762793,0.0006521412,0.0007867672,0.0009315223,0.000437916,0.001103864,0.0009036603,0.0007335365,0.001379023],"category_scores_gemma":[0.002797256,0.0004390351,0.00089375,0.0007567266,0.0006601303,0.0009153241,0.0008376553,0.0008130647,0.0001938664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00147928,"about_ca_system_score_gemma":0.00110299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02294024,"about_ca_topic_score_gemma":0.01911462,"domain_scores_codex":[0.9994499,0.0002143368,0.00004931073,0.00009481786,0.0001374846,0.00005416736],"domain_scores_gemma":[0.9986979,0.0007664349,0.0001502357,0.00009183095,0.0002477202,0.00004587588],"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":[0.00001190643,0.00001692384,0.0007199242,0.00002043039,0.00002080714,0.00002533169,0.00004124204,0.9836141,0.0005901894,0.005024055,0.00006868545,0.009846406],"study_design_scores_gemma":[0.00000128271,0.000006290127,0.00006575562,0.000002440437,0.00000272033,0.000004525746,0.000004444682,0.9987581,0.0001358707,0.0007947963,0.0002211239,0.000002637484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04877261,0.0003616108,0.9449175,0.0001285476,0.00006118452,0.000106852,0.00007846665,0.0004097506,0.005163359],"genre_scores_gemma":[0.823041,0.0003740542,0.1739644,0.00004106091,0.00002679277,0.0002525458,0.00007774861,0.00007344611,0.002148956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02294024,"threshold_uncertainty_score":0.04561347,"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."}}