{"id":"W4405087424","doi":"10.1016/j.trd.2024.104537","title":"Recovery times for highway disruptions due to natural hazard events","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hazard; Natural (archaeology); Natural hazard; Environmental science; Forensic engineering; Transport engineering; Engineering; Geography; Biology; Ecology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001169582,0.0001624947,0.0001985617,0.001172201,0.0004949798,0.0005048643,0.000531167,0.0003579352,0.002409388],"category_scores_gemma":[0.01709471,0.0001305268,0.0003467281,0.00108822,0.0004907465,0.0007219703,0.000685155,0.00100102,0.000322004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468089,"about_ca_system_score_gemma":0.0008287813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1004753,"about_ca_topic_score_gemma":0.1072405,"domain_scores_codex":[0.9992793,0.0001410808,0.00006900055,0.0001219866,0.000216736,0.0001720288],"domain_scores_gemma":[0.9919566,0.002891012,0.003272998,0.0005511725,0.0007851254,0.000543032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007985538,0.0004319799,0.9257374,0.00008375935,0.0002027565,0.0004890254,0.00205141,0.03586144,0.001307128,0.001366317,0.00154421,0.03012595],"study_design_scores_gemma":[0.00001201103,0.0002892064,0.9707854,0.00001959981,0.00003582849,0.0002616954,0.002317928,0.02397145,0.0006256075,0.0005719792,0.001073067,0.00003635331],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983651,0.00005559435,0.0004453564,0.00007307015,0.000001907337,0.00001488612,0.0004535731,0.00001876012,0.0005716906],"genre_scores_gemma":[0.9991942,0.0000304234,0.0001246452,0.000005257481,0.000001124996,0.000007867781,0.000399163,0.000002584138,0.0002347839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1004753,"threshold_uncertainty_score":0.1997809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865570814184447,"score_gpt":0.2870113108676092,"score_spread":0.2683556027257647,"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."}}