{"id":"W4415815001","doi":"10.3390/futuretransp5040161","title":"A Machine Learning Approach to Traffic Congestion Hotspot Identification and Prediction","year":2025,"lang":"en","type":"article","venue":"Future Transportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Hotspot (geology); Traffic congestion; Geospatial analysis; Snapshot (computer storage); Artificial neural network; Deep learning; Convolutional neural network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001229645,0.0001107915,0.00009189243,0.0002418778,0.00007632373,0.00003494283,0.00004869695,0.00008727641,0.000002855122],"category_scores_gemma":[0.00000369659,0.0001211243,0.00002455542,0.0003095632,0.00001108406,0.0001637035,0.000001383533,0.0001414503,0.000002811943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003390191,"about_ca_system_score_gemma":0.00000439891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004507851,"about_ca_topic_score_gemma":0.00003295246,"domain_scores_codex":[0.9993924,0.00001540173,0.00020898,0.0001845856,0.0001004789,0.00009815907],"domain_scores_gemma":[0.9998151,0.000006252656,0.00002155869,0.00008807456,0.00002922636,0.00003975971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0000605168,0.00009682086,0.0021087,0.0005838174,0.0001102602,0.000001351012,0.002861978,0.6143673,0.005538524,0.0182207,0.01149841,0.3445516],"study_design_scores_gemma":[0.0006220831,0.00005512735,0.5162508,0.00007028095,0.0001449921,0.000001514266,0.0004977742,0.3939066,0.0006739409,0.00006586465,0.08747005,0.0002409237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2049899,0.0005970361,0.78109,0.0004070804,0.0009375331,0.0008198709,0.00005324922,0.007604883,0.003500526],"genre_scores_gemma":[0.9971292,0.0004044297,0.001452446,0.00004648081,0.00007633135,0.0001215203,0.0005625567,0.00001422027,0.0001927977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7921394,"threshold_uncertainty_score":0.4939307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004156967358844551,"score_gpt":0.1929750069218384,"score_spread":0.1888180395629939,"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."}}