{"id":"W4200413943","doi":"10.33197/jitter.vol8.iss1.2021.718","title":"PENDETEKSIAN PLAT NOMOR KENDARAAN MENGGUNAKAN ALGORITMA YOU ONLY LOOK ONCE V3 DAN TESSERACT","year":2021,"lang":"id","type":"article","venue":"Jurnal Ilmiah Teknologi Infomasi Terapan","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Humanities; Art; Physics; Artificial intelligence; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0009674257,0.001355843,0.00132414,0.000791165,0.001110897,0.003193195,0.004734694,0.0006522852,0.000122486],"category_scores_gemma":[0.0002711023,0.001373703,0.0007326971,0.002792966,0.0004104353,0.003962374,0.002537166,0.00239578,0.0006035045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006069793,"about_ca_system_score_gemma":0.002101813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008760911,"about_ca_topic_score_gemma":0.0002725635,"domain_scores_codex":[0.9911894,0.0003567609,0.001769921,0.002416301,0.001615648,0.002652006],"domain_scores_gemma":[0.9943668,0.0004016271,0.0006895731,0.002845124,0.000606189,0.001090654],"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":[0.00009261313,0.001288633,0.02941626,0.0003853367,0.0007254372,0.01232292,0.01307247,0.002699641,0.02207905,0.01011232,0.004232188,0.9035732],"study_design_scores_gemma":[0.00569653,0.003201243,0.2234603,0.002125296,0.0003252724,0.01991406,0.002660653,0.2456006,0.06535728,0.001130161,0.4231852,0.007343408],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8089394,0.005629053,0.1426527,0.009416196,0.01562554,0.001049335,0.00008027544,0.002907262,0.01370025],"genre_scores_gemma":[0.9480512,0.0009980737,0.04149899,0.002256132,0.001798252,0.0000398651,0.00005282909,0.0001640088,0.005140658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8962297,"threshold_uncertainty_score":0.9999192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01713776920440893,"score_gpt":0.2445145685401083,"score_spread":0.2273767993356993,"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."}}