{"id":"W4281285560","doi":"10.1007/978-981-19-1004-3_12","title":"Reliability Analysis of Slope Stability Using Censored Samples and Genetic Algorithm","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Randomness; Mathematics; Random variable; Reliability (semiconductor); Stability (learning theory); Probability distribution; Principle of maximum entropy; Probabilistic logic; Statistics; Order statistic; Akaike information criterion; Algorithm; First-order reliability method; Mathematical optimization; Applied mathematics; Computer science; Machine learning","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":[0.002993142,0.0006698853,0.0009994279,0.001644601,0.0003281867,0.0009636222,0.001374746,0.0008825786,0.001149638],"category_scores_gemma":[0.01324919,0.0004609261,0.00107312,0.001382988,0.0008930409,0.0009357766,0.0006850649,0.0008358904,0.0002149441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103052,"about_ca_system_score_gemma":0.0007390699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004719397,"about_ca_topic_score_gemma":0.002527578,"domain_scores_codex":[0.998691,0.0006469138,0.00005159424,0.0001927639,0.0003465128,0.00007125582],"domain_scores_gemma":[0.9939597,0.004400037,0.0004099964,0.0004614472,0.0007218128,0.00004705603],"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":[0.0001118254,0.00002718604,0.001373207,0.00005330835,0.00007773425,0.00004297747,0.00004612978,0.9529925,0.001379006,0.008290562,0.0002663773,0.03533925],"study_design_scores_gemma":[0.000002806402,0.00001177201,0.0003341956,0.000004074487,0.000006330895,0.000007775513,0.000003280778,0.9967182,0.0002823653,0.00257651,0.00004850963,0.000004076147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04333791,0.0003106113,0.9548002,0.00005784663,0.00002120658,0.00002872774,0.00005211127,0.0002910383,0.001100241],"genre_scores_gemma":[0.8396397,0.0002609767,0.1581315,0.00002671979,0.00003245612,0.0000768746,0.000233738,0.0001095142,0.001488577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004719397,"threshold_uncertainty_score":0.01582938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05876801063872297,"score_gpt":0.2758155396777178,"score_spread":0.2170475290389948,"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."}}