{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003946995,0.0001683256,0.0001993874,0.0002105612,0.0001843979,0.00003269946,0.00009739874,0.00007947664,0.0004420932],"category_scores_gemma":[0.000003111661,0.0001532964,0.0001388967,0.0002412685,0.00007892678,0.0002214551,0.000001928267,0.0002620922,0.00006652209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007711953,"about_ca_system_score_gemma":0.00002021187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002418722,"about_ca_topic_score_gemma":0.0002885374,"domain_scores_codex":[0.9985092,0.00002110302,0.0003022225,0.0003624312,0.0003971304,0.0004078742],"domain_scores_gemma":[0.9995265,0.00009632763,0.000006982986,0.0001724966,0.00001933986,0.0001783454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004240223,0.0002323266,0.01846939,0.00295644,0.001149639,0.0002163602,0.006450298,0.8233149,0.01195661,0.006447255,0.01137942,0.1170034],"study_design_scores_gemma":[0.0007529458,0.0004018941,0.5263505,0.0003293219,0.0003294359,0.000005710968,0.0005544691,0.02843885,0.004922614,0.007488371,0.429447,0.0009789163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9196799,0.001199695,0.07562754,0.001162855,0.0003571147,0.0009229595,0.000614135,0.0002209761,0.0002148561],"genre_scores_gemma":[0.9962646,0.0009065922,0.001001403,0.00002094697,0.000102132,0.0003365333,0.0005570811,0.0000312989,0.0007793482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.794876,"threshold_uncertainty_score":0.6251245,"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."}}