{"id":"W636161244","doi":"","title":"Truck Parking In Urban Areas: Application of Choice Modeling Within Traffic Microsimulation","year":2014,"lang":"en","type":"article","venue":"Transportation Research Board 93rd Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Transport engineering; Microsimulation; Parking guidance and information; Enforcement; Parking space; Computer science; Engineering; Automotive 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","sts"],"consensus_categories":[],"category_scores_codex":[0.0143517,0.0004006133,0.0006579596,0.002213219,0.001340493,0.0001835021,0.000805113,0.0005621918,0.00008178102],"category_scores_gemma":[0.001287625,0.0004656095,0.0002174925,0.00443859,0.000932501,0.0012417,0.000007447302,0.001542344,0.00003247563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003394742,"about_ca_system_score_gemma":0.000719552,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0382737,"about_ca_topic_score_gemma":0.1453297,"domain_scores_codex":[0.9880745,0.002545923,0.00217352,0.00122221,0.004443656,0.001540226],"domain_scores_gemma":[0.992255,0.002173001,0.0004885995,0.0005586661,0.003996755,0.0005279905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005203582,0.0003210863,0.2727379,0.0003044002,0.00003276898,0.000008054942,0.07345559,0.6303636,0.001051381,0.01723416,0.0001654097,0.003805329],"study_design_scores_gemma":[0.004489649,0.0005691247,0.5979421,0.001104405,0.00008063145,2.020267e-7,0.05056245,0.3259558,0.001042311,0.003087898,0.01397197,0.001193465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721794,0.0001328682,0.02261779,0.0009663965,0.0001957536,0.002007196,0.0001244944,0.0002885324,0.001487595],"genre_scores_gemma":[0.9940467,0.0001787142,0.00381577,0.00004508038,0.0002969236,0.0003862536,0.0008519533,0.00009599307,0.0002826472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3252043,"threshold_uncertainty_score":0.9999596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226259485218585,"score_gpt":0.3832513437804785,"score_spread":0.3309887489282927,"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."}}