{"id":"W581804495","doi":"","title":"INDUCTANCE-PATTERN RECOGNITION FOR VEHICLE RE-IDENTIFICATION","year":2001,"lang":"en","type":"article","venue":"8th World Congress on Intelligent Transport SystemsITS America, ITS Australia, ERTICO (Intelligent Transport Systems and Services - Europe)","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Waveform; Dynamic time warping; Computer science; Identification (biology); Inductance; Pattern recognition (psychology); Artificial neural network; Detector; Artificial intelligence; Matching (statistics); Process (computing); Signature (topology); Pattern matching; Engineering; Mathematics; Telecommunications; Voltage; Electrical engineering; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006774532,0.001234074,0.001457817,0.000781711,0.0003934461,0.0002976283,0.0006938074,0.0003685947,0.0004649948],"category_scores_gemma":[0.000009178016,0.001243341,0.0003994562,0.001338253,0.0001371524,0.0008493123,0.00001617494,0.0006745415,0.0008727076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001850732,"about_ca_system_score_gemma":0.00003576263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001422141,"about_ca_topic_score_gemma":0.001710506,"domain_scores_codex":[0.99286,0.0001943414,0.003049496,0.001533371,0.001004993,0.001357818],"domain_scores_gemma":[0.9967529,0.0002022654,0.0006727456,0.0008902787,0.0007937493,0.0006881021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007127572,0.006490302,0.2784885,0.09889189,0.01175962,0.004353736,0.0257467,0.2305713,0.0881468,0.002337143,0.005409694,0.2406767],"study_design_scores_gemma":[0.005809318,0.002005748,0.06527073,0.02375351,0.003843599,0.0007777812,0.007465329,0.2255242,0.1128357,0.0001346797,0.541651,0.01092847],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689262,0.001608991,0.01538161,0.0002118593,0.00572155,0.00447882,0.001101617,0.001172029,0.001397303],"genre_scores_gemma":[0.9889415,0.003078443,0.00007849801,0.0001928797,0.0006114095,0.0007012247,0.001609575,0.0003218434,0.004464645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5362412,"threshold_uncertainty_score":0.9999052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0531900500601148,"score_gpt":0.2619268636194741,"score_spread":0.2087368135593594,"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."}}