{"id":"W7099349022","doi":"","title":"ASSESSING RISK AND RESILIENCE FOR TRANSPORTATION INFRASTRUCTURE IN","year":2015,"lang":"en","type":"article","venue":"","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Dangerous goods; Resilience (materials science); Transportation infrastructure; Goods and services; Work (physics); Finished good","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001402866,0.0005761237,0.0002864297,0.002562196,0.001273385,0.002015457,0.001061719,0.0009239484,0.001351952],"category_scores_gemma":[0.007280484,0.0002335833,0.0007095863,0.002547773,0.001841395,0.001568194,0.002398541,0.001087387,0.0001478495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01549166,"about_ca_system_score_gemma":0.007702296,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8237906,"about_ca_topic_score_gemma":0.8644593,"domain_scores_codex":[0.9989203,0.0002324742,0.0000361247,0.0001354588,0.0002144434,0.0004612331],"domain_scores_gemma":[0.997481,0.0006038236,0.0006389661,0.0001519778,0.0006988423,0.0004253335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002144232,0.0001318869,0.8580092,0.00003232253,0.0003878909,0.0004081756,0.0007448823,0.11971,0.0003689654,0.007337785,0.001496725,0.01115781],"study_design_scores_gemma":[0.00001587169,0.0001718796,0.7047876,0.00009411709,0.0001896475,0.0001423397,0.00669677,0.2737536,0.0005863343,0.01073478,0.002751698,0.00007520052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944347,0.0001750049,0.001538003,0.0007294808,0.00000809154,0.00002804594,0.0008011981,0.00001958286,0.002265979],"genre_scores_gemma":[0.999226,0.00006872643,0.0002082407,0.00001326412,0.000001404081,0.000005422155,0.0002143632,0.00000232907,0.0002603229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8237906,"threshold_uncertainty_score":0.3544942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02890228695106986,"score_gpt":0.2858659434741863,"score_spread":0.2569636565231165,"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."}}