{"id":"W2890533060","doi":"10.1109/access.2018.2868610","title":"Real-Time Android Application for Traffic Density Estimation","year":2018,"lang":"en","type":"article","venue":"IEEE Access","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Android (operating system); Computer science; Notation; Artificial intelligence; Embedded system; Real-time computing; Computer graphics (images); Operating system; Mathematics; Arithmetic","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":[0.0002350845,0.00109442,0.0006377997,0.001015132,0.0001661525,0.0003589833,0.0008926266,0.0004866175,0.02154885],"category_scores_gemma":[0.001109857,0.0002270602,0.000329314,0.0003749733,0.0001002122,0.0004991819,0.0005058684,0.0003764225,0.01237213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001883406,"about_ca_system_score_gemma":0.0003129582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002000376,"about_ca_topic_score_gemma":0.002117316,"domain_scores_codex":[0.9997074,0.00003575893,0.00002273486,0.00007285597,0.0001154001,0.00004577862],"domain_scores_gemma":[0.9995939,0.0001169156,0.00002986065,0.00005755971,0.0001620328,0.00003962179],"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":[0.001728695,0.0003810209,0.006320646,0.001553032,0.0001308749,0.001370653,0.0006194726,0.004560077,0.09610575,0.002462411,0.217493,0.6672744],"study_design_scores_gemma":[0.0008143677,0.001092385,0.07662687,0.0004612354,0.0003851867,0.003953022,0.0004547481,0.2576188,0.1922041,0.003153821,0.4626477,0.000587896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0827993,0.002873254,0.4320783,0.0004685455,0.0006365476,0.003347231,0.01746855,0.3932264,0.0671019],"genre_scores_gemma":[0.6587216,0.001604976,0.2286037,0.001027836,0.0004613537,0.005178309,0.02222803,0.00686307,0.07531111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02154885,"threshold_uncertainty_score":0.07208806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03258869564679562,"score_gpt":0.3560541833460245,"score_spread":0.3234654876992289,"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."}}