{"id":"W577251912","doi":"","title":"Looking Out for You: City of Toronto's Deployment Plan for Arterial Traffic Cameras","year":2014,"lang":"fr","type":"article","venue":"Transportation 2014: Past, Present, Future - 2014 Conference and Exhibition of the Transportation Association of Canada // Transport 2014 : Du passé vers l'avenir - 2014 Congrès et Exposition de 'Association des transports du Canada","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software deployment; Plan (archaeology); Traffic congestion; Transport engineering; Traffic flow (computer networking); Key (lock); Computer science; Street network; Computer security; Engineering; Geography","routes":{"ca_aff":false,"ca_fund":false,"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":[0.002515553,0.001109177,0.0001950386,0.002142168,0.003445487,0.003998172,0.001429372,0.003424557,0.01528322],"category_scores_gemma":[0.002609979,0.000728995,0.0005100865,0.001446907,0.001106871,0.002082134,0.001628573,0.002360025,0.004760361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02060268,"about_ca_system_score_gemma":0.07945053,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7070757,"about_ca_topic_score_gemma":0.8382686,"domain_scores_codex":[0.9980782,0.0001985582,0.0001096392,0.0001188344,0.0009194371,0.0005753064],"domain_scores_gemma":[0.9945023,0.0002007877,0.0002053993,0.00009999076,0.00337494,0.001616462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000127438,0.0002003415,0.006487423,0.001108011,0.00001914607,0.001802059,0.002271332,0.004346727,0.01011824,0.01692723,0.8421162,0.1144759],"study_design_scores_gemma":[0.00003930874,0.0001946031,0.02252326,0.0003982843,0.00002316499,0.0002353482,0.004364482,0.0009234494,0.001332944,0.0005338759,0.9693574,0.0000739078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07562137,0.02250953,0.05190396,0.245736,0.0143696,0.0168599,0.01579044,0.003524768,0.5536845],"genre_scores_gemma":[0.2280895,0.03226511,0.09804849,0.02621471,0.001575341,0.004482844,0.01820599,0.0006820875,0.5904359],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2929243,"threshold_uncertainty_score":0.5892987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006929927348250636,"score_gpt":0.2006220994430869,"score_spread":0.1936921720948363,"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."}}