{"id":"W2024744504","doi":"10.1007/s10064-014-0570-3","title":"An expert judgement approach to determining the physical vulnerability of roads to debris flow","year":2014,"lang":"en","type":"article","venue":"Bulletin of Engineering Geology and the Environment","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Golder Associates (Canada)","funders":"European Commission","keywords":"Fragility; Debris flow; Debris; Vulnerability (computing); Judgement; Environmental science; Risk analysis (engineering); Statistics; Forensic engineering; Computer science; Geography; Mathematics; Engineering; Business; Meteorology; Physics","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":[0.04541377,0.001271077,0.001606083,0.01093889,0.004340939,0.004403895,0.003800437,0.002723091,0.01066599],"category_scores_gemma":[0.1506586,0.0007827269,0.002192229,0.00490498,0.002988771,0.001794659,0.002998443,0.002250361,0.001375507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004352289,"about_ca_system_score_gemma":0.007709485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01748747,"about_ca_topic_score_gemma":0.03779969,"domain_scores_codex":[0.9425092,0.03588375,0.004403386,0.002410013,0.01336782,0.001425849],"domain_scores_gemma":[0.7822268,0.1741343,0.003740622,0.003883524,0.03383594,0.002178845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002343334,0.002299475,0.04524799,0.00556373,0.002243555,0.003303274,0.04651826,0.09599495,0.009704188,0.09190956,0.0341805,0.6606911],"study_design_scores_gemma":[0.001056056,0.002187865,0.03556769,0.002955477,0.00153702,0.002369271,0.03773462,0.5187131,0.006275679,0.3421044,0.0487451,0.0007537993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1665868,0.0008152524,0.7408465,0.002909927,0.0004475701,0.005439979,0.001410695,0.0003861199,0.0811572],"genre_scores_gemma":[0.4221025,0.0002609457,0.5698879,0.0005393251,0.000140415,0.00147336,0.0004914012,0.00005190446,0.00505223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04541377,"threshold_uncertainty_score":0.2401739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003926636126975414,"score_gpt":0.183850332912148,"score_spread":0.1799236967851726,"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."}}