{"id":"W2587580629","doi":"10.22215/etd/2007-06684","title":"Bus real-time arrival prediction using statistical pattern recognition technique","year":2007,"lang":"en","type":"dissertation","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Computer science; Arrival time; Pattern recognition (psychology); Artificial intelligence; Engineering; Transport engineering","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":[0.0002811996,0.0004765193,0.0004110936,0.000956155,0.0001548592,0.0004587496,0.0004343826,0.0002952351,0.001485337],"category_scores_gemma":[0.001145094,0.0002048139,0.0003755125,0.0008559027,0.0001102201,0.0005469084,0.0001820067,0.0005184522,0.001150115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002209303,"about_ca_system_score_gemma":0.0005271366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005718824,"about_ca_topic_score_gemma":0.004930016,"domain_scores_codex":[0.9997761,0.00003361077,0.0000188911,0.00005143344,0.00008413699,0.00003580176],"domain_scores_gemma":[0.9994354,0.0001660549,0.00006850621,0.00007064626,0.0002360852,0.00002327839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003549218,0.0002115972,0.005829234,0.00006634016,0.00007542904,0.0001673711,0.00005650069,0.1313151,0.04545008,0.001562845,0.005327639,0.8095831],"study_design_scores_gemma":[0.00000808604,0.00008200701,0.001664655,0.000004768971,0.0000156168,0.00006052668,0.00001232084,0.9873368,0.009599805,0.0003426093,0.0008649887,0.000007787577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1272327,0.0003945255,0.8634225,0.0002045375,0.0002093604,0.00005630358,0.0003045684,0.005272011,0.002903498],"genre_scores_gemma":[0.7730548,0.0004527504,0.2182482,0.0000612997,0.00007758953,0.00007050184,0.0009562028,0.0001027067,0.006975923],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005718824,"threshold_uncertainty_score":0.01137108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351979009141932,"score_gpt":0.2661416219642892,"score_spread":0.2526218318728699,"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."}}