{"id":"W1597932877","doi":"","title":"Modeling and Analysis of Truck Weight and Credential Screening System","year":2008,"lang":"en","type":"article","venue":"Transportation Research Board 87th Annual MeetingTransportation Research Board","topic":"Transport Systems and Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Credential; Bridge (graph theory); Port (circuit theory); Engineering; Process (computing); Computer science; Transport engineering; Simulation; Automotive engineering; Operations research; Computer security; Electrical engineering","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":[0.0008834183,0.0006570381,0.0007761103,0.0007966047,0.0007930996,0.001510818,0.001404404,0.001309989,0.003925424],"category_scores_gemma":[0.002599046,0.0005378628,0.0008251828,0.0005458104,0.0007539029,0.001257433,0.0007653101,0.0009190522,0.0004538011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003085506,"about_ca_system_score_gemma":0.003600081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0797701,"about_ca_topic_score_gemma":0.02358517,"domain_scores_codex":[0.9993424,0.000175783,0.00002378119,0.0001006159,0.0001865278,0.0001707748],"domain_scores_gemma":[0.9989505,0.0004564342,0.0001776682,0.00005904558,0.0002732433,0.0000830161],"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":[0.00001897721,0.00002149416,0.0008787469,0.000008268737,0.000005413071,0.00003634786,0.00002618618,0.9951072,0.0003746758,0.002562995,0.00009822435,0.000861556],"study_design_scores_gemma":[0.000006110501,0.00001385787,0.0002678357,0.000001955216,0.000004254125,0.000006499894,0.00001478444,0.9988067,0.0001712838,0.0004919386,0.0002101861,0.000004645109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5756393,0.0002718894,0.3781665,0.0008927922,0.00006953938,0.000427339,0.001191701,0.0007744976,0.0425664],"genre_scores_gemma":[0.9823766,0.0001520283,0.008283962,0.00003621578,0.000007713993,0.0001480865,0.0002653742,0.00003603471,0.008693948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0797701,"threshold_uncertainty_score":0.1586115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04257861955072401,"score_gpt":0.3094898080093311,"score_spread":0.2669111884586071,"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."}}