{"id":"W4416332798","doi":"10.2139/ssrn.5768078","title":"Machine Learning-Based Prediction for the Permanent Maximum Displacement of Slopes Subjected to Earthquake","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ground motion; Displacement (psychology); Finite element method; Nonlinear system; Nonlinear regression; Boosting (machine learning); Linear regression","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006561934,0.0004751176,0.0006415182,0.0006299015,0.000227654,0.0005173265,0.0005556279,0.000863893,0.001235184],"category_scores_gemma":[0.002858501,0.0002870237,0.0003779578,0.0005033269,0.0002680767,0.0004361728,0.0003842818,0.0006776375,0.0003546414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003978061,"about_ca_system_score_gemma":0.0004620022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008549551,"about_ca_topic_score_gemma":0.005671441,"domain_scores_codex":[0.9998391,0.00003605192,0.00001471234,0.00005747914,0.00002187687,0.00003075915],"domain_scores_gemma":[0.9982667,0.001302701,0.0001383391,0.00005707224,0.0001790405,0.00005612449],"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":[0.0001477303,0.00009340368,0.01012204,0.00003325142,0.00003475924,0.0000399057,0.00001654038,0.9470879,0.0008950806,0.0003487723,0.000539754,0.04064084],"study_design_scores_gemma":[0.000001346306,0.000008580592,0.001130328,0.000001324218,0.000001331473,0.000002326372,0.000001948709,0.9986205,0.0000834626,0.0001368895,0.00001064389,0.000001240035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8019628,0.0005502001,0.1941513,0.0003691837,0.00009977617,0.00003871313,0.000592842,0.0006270355,0.001608131],"genre_scores_gemma":[0.9945069,0.00005363897,0.004586842,0.00001187366,0.00002240278,0.00001394007,0.0002616411,0.000008263512,0.0005344892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008549551,"threshold_uncertainty_score":0.01699954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006139873326517312,"score_gpt":0.2282479576231822,"score_spread":0.2221080842966649,"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."}}