{"id":"W171464381","doi":"","title":"2008 Travel Time Study: Advances in System Performance Measurement","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Truck; Global Positioning System; Data collection; Travel time; Computer science; Christian ministry; Process (computing); Operations research; Engineering; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004133271,0.0008405685,0.0007853055,0.002971,0.0004377354,0.001717846,0.0009995479,0.0008951378,0.002236621],"category_scores_gemma":[0.01809648,0.0003159037,0.0005362385,0.005576629,0.0003646657,0.002016616,0.001215015,0.001622885,0.0007976718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002373232,"about_ca_system_score_gemma":0.002404584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02542559,"about_ca_topic_score_gemma":0.0168438,"domain_scores_codex":[0.9947536,0.002244937,0.0003889856,0.0007672614,0.001711254,0.0001339445],"domain_scores_gemma":[0.9865145,0.004494296,0.001829858,0.001335428,0.005381293,0.0004445544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002803506,0.0006653391,0.2273711,0.001039768,0.0003090779,0.0000978775,0.001572325,0.01868899,0.002439805,0.01275794,0.02302653,0.7117509],"study_design_scores_gemma":[0.000124312,0.003027768,0.6632608,0.0008258629,0.0003212573,0.0007146075,0.002632188,0.1353074,0.005177967,0.008977203,0.1793863,0.0002443323],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5362877,0.01953742,0.3325077,0.01106174,0.001296321,0.00135941,0.01645875,0.001535814,0.07995517],"genre_scores_gemma":[0.8124439,0.009521974,0.1581739,0.001001608,0.0009524513,0.0009323063,0.009345679,0.0002527596,0.007375469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02542559,"threshold_uncertainty_score":0.05055517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02991996478993719,"score_gpt":0.3140567953580833,"score_spread":0.2841368305681461,"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."}}