{"id":"W4410797962","doi":"10.1016/j.ress.2025.111296","title":"Improved genetic programming modeling of slope stability and landslide susceptibility","year":2025,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Landslide; Genetic programming; Stability (learning theory); Slope stability; Computer science; Geotechnical engineering; Geology; Artificial intelligence; 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":[0.0003514197,0.000433592,0.0005119914,0.00040101,0.0003483817,0.0006591678,0.000927688,0.0009754922,0.002298596],"category_scores_gemma":[0.001718129,0.0003628721,0.0004981518,0.0005038437,0.0004758811,0.0004304574,0.0003416833,0.0007557642,0.0001721975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009786288,"about_ca_system_score_gemma":0.0009832287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03332619,"about_ca_topic_score_gemma":0.02081884,"domain_scores_codex":[0.9998953,0.00003840958,0.000003123902,0.00002299752,0.00001920734,0.00002099575],"domain_scores_gemma":[0.9992813,0.0005121716,0.00005662163,0.00001798355,0.0001064001,0.00002551908],"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":[0.000003480417,0.000007289916,0.000153358,0.000002077812,0.000003655218,0.000008891898,0.000004197356,0.9979776,0.0001180213,0.0008753733,0.00003373364,0.0008123413],"study_design_scores_gemma":[0.000001409452,0.000001806582,0.00004736595,4.183515e-7,0.000001516889,0.00000103712,9.992783e-7,0.9995627,0.00002772669,0.0003340781,0.00002007631,7.459423e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5865369,0.0002770971,0.3956456,0.0005611062,0.00007918802,0.00004103834,0.0002556845,0.0003332983,0.01627006],"genre_scores_gemma":[0.9713833,0.00008563331,0.02363042,0.00004785605,0.00001742197,0.00003589401,0.00007492042,0.00004986228,0.004674819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03332619,"threshold_uncertainty_score":0.06626439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004253058661254786,"score_gpt":0.1884968161907006,"score_spread":0.1842437575294459,"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."}}