{"id":"W2371529211","doi":"","title":"Research on automatic toll charging system based on computer vision","year":2002,"lang":"en","type":"article","venue":"","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Toll; License; Software; Computer science; Computer vision; Artificial intelligence; Sampling (signal processing); Image (mathematics); Image processing; Computer graphics (images); Operating system; Filter (signal processing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000557538,0.0002655863,0.0003580273,0.0006964703,0.0002702152,0.0008062623,0.0005265144,0.0009134206,0.002904812],"category_scores_gemma":[0.0007474152,0.0002107383,0.000298044,0.0004938787,0.0003831778,0.001202915,0.0001688827,0.0004580325,0.0009266947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003776912,"about_ca_system_score_gemma":0.0004554257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001283994,"about_ca_topic_score_gemma":0.000662634,"domain_scores_codex":[0.9994785,0.0001188992,0.00001664086,0.00009739205,0.0002330168,0.00005551053],"domain_scores_gemma":[0.9995825,0.0000998062,0.00001680993,0.00002408796,0.0002522876,0.00002456281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002375383,0.000407888,0.002845614,0.0006218301,0.00008270356,0.0003454349,0.0003392583,0.007563173,0.2979999,0.02336033,0.00624886,0.6599473],"study_design_scores_gemma":[0.0002741595,0.002746505,0.01617528,0.0002869997,0.000226856,0.003467024,0.0004488329,0.4183829,0.3854591,0.01815577,0.1541591,0.0002175955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1340948,0.01052119,0.8102972,0.001307099,0.0006946253,0.0002430869,0.00007483095,0.002405847,0.04036127],"genre_scores_gemma":[0.6900705,0.008135666,0.2721817,0.0006201009,0.0005261173,0.0001978174,0.0003066197,0.0001016711,0.02785975],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002904812,"threshold_uncertainty_score":0.009717524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04387523956958098,"score_gpt":0.2766920019944895,"score_spread":0.2328167624249085,"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."}}