{"id":"W4245006233","doi":"10.32920/ryerson.14657370","title":"A downtown on-street parking model with urban truck delivery effects","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Downtown; Truck; Transport engineering; Traffic congestion; Parking guidance and information; Business; Destinations; Computer science; Engineering; Geography; Tourism; Automotive engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002776876,0.0009420296,0.0007629247,0.0004347654,0.000650641,0.001494414,0.002196471,0.001748791,0.006730684],"category_scores_gemma":[0.0006178604,0.0007052748,0.0008301277,0.0007155723,0.0009780206,0.001030336,0.001454083,0.001020083,0.0005845379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003193473,"about_ca_system_score_gemma":0.001930113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1182954,"about_ca_topic_score_gemma":0.09619921,"domain_scores_codex":[0.9997715,0.00006329083,0.000006942827,0.00005106289,0.00003050803,0.00007672402],"domain_scores_gemma":[0.9997491,0.00006369947,0.00003695369,0.0000134177,0.00005606051,0.00008073806],"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":[0.00007632811,0.00004033718,0.0008090241,0.00002709955,0.00001570716,0.0002542187,0.00004587641,0.9835595,0.0005582216,0.01304005,0.0006539202,0.0009197384],"study_design_scores_gemma":[0.00002419675,0.00002569274,0.000357735,0.000005000454,0.00001566232,0.00002667602,0.00006736728,0.9970902,0.0001061082,0.001502003,0.0007698121,0.000009527752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7700242,0.0007287265,0.1430855,0.001723426,0.0001836897,0.0002723334,0.002538314,0.0002431492,0.08120061],"genre_scores_gemma":[0.9670815,0.0002545185,0.004338955,0.00006886194,0.00001760618,0.00008085986,0.00030729,0.00003258536,0.02781786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1182954,"threshold_uncertainty_score":0.2352136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01618811842824774,"score_gpt":0.2290001756225961,"score_spread":0.2128120571943483,"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."}}