{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002732707,0.0004021843,0.001019714,0.003465764,0.0007447856,0.00005859582,0.0003926929,0.0004452444,0.00005985568],"category_scores_gemma":[0.00005562809,0.0004223581,0.0002397363,0.003679386,0.0009056354,0.0005582872,0.00001213989,0.001236109,0.000005480334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008505903,"about_ca_system_score_gemma":0.0001151654,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007993132,"about_ca_topic_score_gemma":0.005458389,"domain_scores_codex":[0.9937199,0.0003400576,0.001461254,0.0008695946,0.002397489,0.001211684],"domain_scores_gemma":[0.9968923,0.0003947471,0.0001078734,0.0004943035,0.001589347,0.0005213745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000972633,0.0002021447,0.7807159,0.004375907,0.003357396,0.0007424009,0.02349173,0.1557101,0.007389243,0.01714991,0.0005174401,0.005375274],"study_design_scores_gemma":[0.001889624,0.0003371639,0.8016453,0.0004354505,0.000512576,0.000005926839,0.01027167,0.1813526,0.00156435,0.0001186945,0.001215464,0.0006511656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9751682,0.001414871,0.02079839,0.0001027468,0.0001036522,0.0008872803,0.0005517601,0.0004994784,0.0004736797],"genre_scores_gemma":[0.9943772,0.001644089,0.003191468,0.000004541752,0.00007425955,0.0001906958,0.0003322633,0.00009324576,0.00009223444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02564249,"threshold_uncertainty_score":0.9998228,"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."}}