{"id":"W7008014102","doi":"","title":"Analyzing Impact of the COVID-19 Pandemic on Traffic Congestion and Commercial Vehicle Travel Patterns within the Greater Toronto and Hamilton Area","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Transport Canada","keywords":"Destinations; Bottleneck; Traffic congestion; Pandemic; Global Positioning System; Travel time; Coronavirus disease 2019 (COVID-19)","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0002329979,0.0002231771,0.0001653662,0.0007181978,0.0006324732,0.0009282067,0.0003186575,0.0002141716,0.001799246],"category_scores_gemma":[0.001138298,0.0001141352,0.0002134316,0.00200916,0.0003076076,0.0002474689,0.0003994055,0.0003187733,0.0002415378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007675911,"about_ca_system_score_gemma":0.006209861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9367602,"about_ca_topic_score_gemma":0.9692509,"domain_scores_codex":[0.9997639,0.00002455926,0.000005784806,0.00003284562,0.00008970443,0.00008306984],"domain_scores_gemma":[0.9995083,0.00008063076,0.00005510719,0.00002291219,0.0002442154,0.00008878515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001548939,0.00008727235,0.8995918,0.0001360712,0.0001090434,0.0003915922,0.002941776,0.02260733,0.001808831,0.001764652,0.01399891,0.05640776],"study_design_scores_gemma":[0.0000033903,0.00003808203,0.9739896,0.00003725788,0.00002106814,0.00002328565,0.005386393,0.01513841,0.0004480644,0.0001057722,0.004795347,0.00001329582],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889907,0.0001996391,0.0003756981,0.0003646746,0.00001078585,0.00003558522,0.003386559,0.00002370828,0.006612819],"genre_scores_gemma":[0.991694,0.0004328221,0.0006025882,0.00003856013,0.000007986114,0.00001942875,0.00357829,0.00001046013,0.003615893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06323981,"threshold_uncertainty_score":0.1272244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03357869606730481,"score_gpt":0.3193879434027367,"score_spread":0.2858092473354319,"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."}}