{"id":"W2083910000","doi":"10.1139/t10-044","title":"Practical reliability analysis of slope stability by advanced Monte Carlo simulations in a spreadsheet","year":2010,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geotechnical Engineering and Analysis","field":"Engineering","cited_by":337,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monte Carlo method; Reliability (semiconductor); Slope stability; Factor of safety; Slip (aerodynamics); Slope stability analysis; Reliability engineering; Stability (learning theory); Geotechnical engineering; Software; Computer science; Statistics; Engineering; Mathematics","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":[0.001109155,0.0005831404,0.0004890269,0.0007177127,0.0002913498,0.0005992548,0.0008998313,0.0004837524,0.005600591],"category_scores_gemma":[0.005589442,0.0004073995,0.0003952109,0.0006231353,0.0002239293,0.0006876227,0.0003332432,0.0007400206,0.00107327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000410297,"about_ca_system_score_gemma":0.0009425567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003551826,"about_ca_topic_score_gemma":0.002516906,"domain_scores_codex":[0.9995444,0.0001642928,0.00003272031,0.00005286517,0.0001820527,0.00002354684],"domain_scores_gemma":[0.9956493,0.002949537,0.0001911948,0.0004149838,0.0007585954,0.00003644954],"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":[0.00007167806,0.00005287104,0.001269341,0.00007393038,0.00003444455,0.00007117983,0.00008638178,0.9221113,0.005340281,0.01351305,0.001876816,0.05549867],"study_design_scores_gemma":[0.000008210727,0.00001464416,0.0001866181,0.00001023353,0.000007192694,0.00002282089,0.000005522461,0.9937262,0.00206381,0.002483801,0.00146582,0.000005194991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02432933,0.00004219614,0.9696738,0.000044476,0.00001031281,0.00006835765,0.0001855846,0.002206005,0.003440077],"genre_scores_gemma":[0.2769403,0.0002306189,0.7170494,0.00006673163,0.00002433897,0.000507403,0.0005913327,0.0006049644,0.003984885],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005600591,"threshold_uncertainty_score":0.01873589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007820072684598304,"score_gpt":0.2361561567607075,"score_spread":0.2283360840761092,"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."}}