{"id":"W2164481248","doi":"10.1139/cjce-2015-0216","title":"Probabilistic assessment of a design truck model and live load factor from weigh-in-motion data for Mexican Highway bridge design","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidad de Guanajuato; Consejo Nacional de Ciencia y Tecnología","keywords":"Weigh in motion; Bridge (graph theory); Truck; Reliability (semiconductor); Engineering; Design load; Calibration; Structural load; Probabilistic logic; Transport engineering; Statistical model; Reliability engineering; Computer science; Civil engineering; Automotive engineering; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004334053,0.0001722852,0.0003223808,0.0002167457,0.00001457668,0.0000291987,0.0002633581,0.00007900741,0.000008057658],"category_scores_gemma":[0.0002466425,0.0001714857,0.00003424793,0.00006957871,0.00002073091,0.0003043535,0.00001483674,0.0002133651,1.674496e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008663805,"about_ca_system_score_gemma":0.001019005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008263151,"about_ca_topic_score_gemma":0.008467233,"domain_scores_codex":[0.9989902,0.0000178008,0.0003857796,0.0001384312,0.0001579098,0.0003098579],"domain_scores_gemma":[0.999024,0.0001195003,0.00008738255,0.0002218008,0.000157137,0.0003901241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001018123,0.000002950445,0.0003545492,0.00006834036,0.00004955571,0.00001600185,0.0007033013,0.995881,0.001553227,0.0001079424,0.0006928397,0.0005600674],"study_design_scores_gemma":[0.0006374276,0.00007830228,0.007128147,0.0002573665,0.00003874598,0.00001808032,0.00004940738,0.9902772,0.0003455991,0.0006726815,0.0003132055,0.0001838607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05518334,0.0009289708,0.942664,0.00001657609,0.0007742007,0.0002462224,0.0001204552,0.0000178377,0.00004836457],"genre_scores_gemma":[0.9500349,0.00002333221,0.04968847,0.000004535136,0.0001951255,0.000006689808,0.000007148293,0.00003688501,0.000002871817],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8948516,"threshold_uncertainty_score":0.6992985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05344859658508205,"score_gpt":0.2458519846831995,"score_spread":0.1924033880981174,"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."}}