{"id":"W1810285639","doi":"10.1139/cjce-2014-0447","title":"Hybrid short-term freeway speed prediction methods based on periodic analysis","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Residual; Autoregressive model; Computer science; Term (time); Time series; Moving average; Data mining; Multivariate statistics; Algorithm; Econometrics; Machine learning; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006090542,0.0001852853,0.0002933402,0.001649486,0.0000368732,0.00008252788,0.0002215777,0.00006627608,0.00006831697],"category_scores_gemma":[0.00008689733,0.0001972512,0.0001923267,0.0004563181,0.00001949578,0.0001888503,0.000005552789,0.00030723,0.00000303261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004074746,"about_ca_system_score_gemma":0.0001499571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007175878,"about_ca_topic_score_gemma":0.003304253,"domain_scores_codex":[0.9989673,0.00002905865,0.0003774577,0.0001125365,0.0002211471,0.0002924521],"domain_scores_gemma":[0.9988361,0.00002900413,0.00004214038,0.0002199267,0.00009386778,0.0007789876],"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":[0.000003556171,0.000005345717,0.001126298,0.00002226757,0.0002677033,0.00008654095,0.00009501779,0.9823813,0.0003656207,0.00004868988,0.01267909,0.002918609],"study_design_scores_gemma":[0.0002548796,0.00009770765,0.005117412,0.00006470281,0.0002835339,0.00002896042,0.00002609087,0.9726631,0.0008831294,0.000008987719,0.02038615,0.0001853299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01456823,0.0003487268,0.9766998,0.00005808466,0.001366474,0.00009910447,0.00003447622,0.0007381578,0.006086905],"genre_scores_gemma":[0.9947358,0.00001535466,0.004932152,0.00003869645,0.0002040969,0.000003184773,0.0000119681,0.00003804303,0.00002064107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9801676,"threshold_uncertainty_score":0.8043671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660196522321184,"score_gpt":0.2336306931378454,"score_spread":0.2170287279146335,"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."}}