{"id":"W3035248757","doi":"10.24963/ijcai.2020/462","title":"Predicting Landslides Using Locally Aligned Convolutional Neural Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Compute Canada","keywords":"Convolutional neural network; Landslide; Pattern recognition (psychology); Orientation (vector space); Artificial neural network; Georeference; Pixel","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":[0.0003911835,0.0008734425,0.0004029067,0.001226004,0.0001961415,0.0004994815,0.0007639181,0.0006106691,0.0006394733],"category_scores_gemma":[0.001055843,0.0002588547,0.0004238983,0.0009465249,0.0002169069,0.0006707704,0.0003431478,0.0005107358,0.0002684782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003935,"about_ca_system_score_gemma":0.0005835106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03344646,"about_ca_topic_score_gemma":0.05533209,"domain_scores_codex":[0.9998013,0.00002113004,0.00001139013,0.00007882113,0.00004311535,0.00004410133],"domain_scores_gemma":[0.9995719,0.000124283,0.00009608553,0.00004699961,0.0001370271,0.00002381016],"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":[0.0001595726,0.0002172074,0.023509,0.00004584931,0.0001127166,0.0001243867,0.00002486537,0.857294,0.00673146,0.0004049212,0.002549512,0.1088265],"study_design_scores_gemma":[0.000002236728,0.00001073855,0.002778552,0.000003226471,0.000008445349,0.000007969532,0.00000624348,0.9957534,0.001092931,0.0002174413,0.0001154163,0.00000337856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8111649,0.001050609,0.1787764,0.0003700539,0.00009857174,0.00005591944,0.002304249,0.003353893,0.002825399],"genre_scores_gemma":[0.9725096,0.0001829133,0.0234901,0.00005330396,0.00002382855,0.00001862489,0.002259343,0.00002782743,0.001434444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03344646,"threshold_uncertainty_score":0.06650358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482891463452492,"score_gpt":0.2145370287442684,"score_spread":0.1997081141097435,"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."}}