{"id":"W4407397324","doi":"10.3390/geosciences15020057","title":"Tools for Predicting Long Runout Landslides","year":2025,"lang":"en","type":"article","venue":"Geosciences","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"BGC Engineering (Canada)","funders":"U.S. Forest Service; U.S. Geological Survey; Colorado Scientific Society","keywords":"Landslide; Geology; 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":[0.0003791508,0.00007775735,0.00009135919,0.00003098753,0.00037907,0.0001504383,0.000286119,0.00005420564,0.0002855776],"category_scores_gemma":[0.0001620282,0.00005162766,0.00005197406,0.0003097752,0.0001790181,0.0003352948,0.0001282819,0.00005996688,0.00005208338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003418962,"about_ca_system_score_gemma":0.0000218961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002334236,"about_ca_topic_score_gemma":0.0001981793,"domain_scores_codex":[0.9991248,0.00001152771,0.0001398887,0.0002632871,0.0001749957,0.0002855495],"domain_scores_gemma":[0.999644,0.0001394363,0.0000402022,0.0001229275,0.000006637757,0.00004678711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002161306,0.00004198339,0.8549656,0.00001919646,0.0000135072,0.000003345915,0.0005734056,0.001301326,0.001102809,0.0006576748,0.004518622,0.1367809],"study_design_scores_gemma":[0.0007547768,0.0001707336,0.7774873,0.0001070313,0.0000494855,0.000008573251,0.0007739898,0.01418784,0.0028352,0.004551,0.1987247,0.0003493239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9465119,0.0001713881,0.005587558,0.0006744464,0.0006738185,0.0002477826,0.000009980147,0.00007212917,0.04605096],"genre_scores_gemma":[0.9912608,0.00004488588,0.001383027,0.0002960131,0.00004088607,0.00002628648,0.000003688729,0.000003076845,0.006941382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1942061,"threshold_uncertainty_score":0.3126875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075567097890891,"score_gpt":0.2480739360868747,"score_spread":0.2373182651079658,"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."}}