{"id":"W4402986541","doi":"10.1080/00207721.2024.2408551","title":"Landslide spatial prediction based on cascade forest and stacking ensemble learning algorithm","year":2024,"lang":"en","type":"article","venue":"International Journal of Systems Science","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Cascade; Landslide; Ensemble learning; Random forest; Algorithm; Computer science; Artificial intelligence; Stacking; Machine learning; Pattern recognition (psychology); Geology; Engineering; Geomorphology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001017815,0.00007786884,0.00009065215,0.0001859822,0.0001249136,0.0003552847,0.0002643365,0.00004147881,0.00004341008],"category_scores_gemma":[0.00007498867,0.00005277442,0.00004141833,0.0001839921,0.0001493452,0.0004789881,0.00006626281,0.0002533764,0.000025955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000278301,"about_ca_system_score_gemma":0.00006829241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002784771,"about_ca_topic_score_gemma":0.00001320214,"domain_scores_codex":[0.9982955,0.00003061189,0.0002727811,0.0001766619,0.001078368,0.0001460654],"domain_scores_gemma":[0.9995759,0.00007937576,0.0001292979,0.00005166464,0.00006376672,0.0001000529],"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":[0.00009408264,0.00007233306,0.1330675,0.0000294458,0.00007486802,0.0008493322,0.001189018,0.6737142,0.01927222,0.0002992885,0.001255795,0.1700819],"study_design_scores_gemma":[0.0003251586,0.0002520577,0.01948736,0.000492469,0.00001351698,0.0007723901,0.0001351849,0.9585118,0.0006340789,0.00007443643,0.01921101,0.00009053365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8421715,0.00043735,0.1397908,0.0007365207,0.009996345,0.0001506056,0.00001972019,0.00005511121,0.006642081],"genre_scores_gemma":[0.9987457,0.00005035605,0.0004678411,0.00003194465,0.000467113,0.000001184168,0.000001258925,0.0000067189,0.0002279046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2847976,"threshold_uncertainty_score":0.3426019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006549653312501752,"score_gpt":0.237861202095653,"score_spread":0.2313115487831513,"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."}}