{"id":"W2106915574","doi":"","title":"Syntactic inference for highway traffic analysis","year":2009,"lang":"en","type":"article","venue":"International Conference on Information Fusion","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Classifier (UML); Estimator; Artificial intelligence; Markov chain; Inference; Hidden Markov model; Machine learning; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00190124,0.0006148841,0.0006815961,0.002356479,0.0008952649,0.001376751,0.00127659,0.0009485377,0.0035274],"category_scores_gemma":[0.008160667,0.0004751187,0.001685936,0.001501697,0.001213383,0.002249083,0.001148889,0.001478879,0.001079723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593215,"about_ca_system_score_gemma":0.002006919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008927304,"about_ca_topic_score_gemma":0.006998876,"domain_scores_codex":[0.9982842,0.0006643479,0.0001364412,0.0003966653,0.0004196424,0.00009869904],"domain_scores_gemma":[0.9965022,0.00225119,0.0002344894,0.0004428051,0.0005123342,0.00005699734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001212973,0.0001347426,0.008004087,0.0003688575,0.000201014,0.0005746785,0.0006026253,0.2061606,0.008400989,0.3967643,0.01398655,0.3646803],"study_design_scores_gemma":[0.000008948329,0.00001613536,0.0006628226,0.00003351308,0.00002604218,0.00008463197,0.00005648501,0.781386,0.001747909,0.2105445,0.005407961,0.00002507518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009863861,0.0002801151,0.9846104,0.0003821708,0.00004737611,0.00006039235,0.0007571855,0.002202955,0.001795511],"genre_scores_gemma":[0.39951,0.0004531616,0.5921223,0.000467255,0.0001518104,0.0002768659,0.003861072,0.0005761435,0.002581419],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008927304,"threshold_uncertainty_score":0.01775068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670258564401325,"score_gpt":0.2681093774615749,"score_spread":0.2514067918175616,"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."}}