{"id":"W3166058195","doi":"10.1177/03611981211014525","title":"Incorporating Flood Hazards into Pavement Sustainability Assessment","year":2021,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Waterloo","funders":"","keywords":"Sustainability; Environmental science; Flooding (psychology); Life-cycle assessment; Climate change; Resilience (materials science); Flood myth; Greenhouse gas; Civil engineering; Environmental impact assessment; Slab; Engineering; Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.005827481,0.0002684509,0.0005316226,0.0006876205,0.0007757942,0.0002134513,0.0008431252,0.0002011948,0.0004415816],"category_scores_gemma":[0.000305761,0.0002121771,0.0005139206,0.003118574,0.0005574716,0.0006839249,0.00001215232,0.002830669,0.000006995834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052458,"about_ca_system_score_gemma":0.001977275,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002910034,"about_ca_topic_score_gemma":0.04186425,"domain_scores_codex":[0.9918286,0.001438319,0.001593324,0.0004129198,0.003877166,0.0008496581],"domain_scores_gemma":[0.9908593,0.0006862605,0.00023417,0.0006792788,0.007170219,0.0003708163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002909257,0.0005102109,0.60813,0.001984115,0.0007318396,0.0005415581,0.004697478,0.2975242,0.02817744,0.008957283,0.003739124,0.04471584],"study_design_scores_gemma":[0.001167626,0.000323388,0.9317105,0.0002465183,0.0001041262,0.000001082737,0.008847454,0.00541159,0.0147432,0.0316788,0.00545505,0.0003106984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744085,0.0002705583,0.02104653,0.00292957,0.0004658094,0.0005685059,0.00002719983,0.00004608335,0.0002372208],"genre_scores_gemma":[0.9929568,0.0004207758,0.00610368,0.00002957393,0.0001952481,0.00006339286,0.00002855713,0.00004498251,0.0001570403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3235804,"threshold_uncertainty_score":0.9994698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02996486790779782,"score_gpt":0.3690492741977712,"score_spread":0.3390844062899733,"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."}}