{"id":"W4391719216","doi":"10.21608/jocc.2024.339920","title":"Handwritten Arabic Bills Reader and Recognizer","year":2024,"lang":"en","type":"article","venue":"Journal of Computing and Communication","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Arabic; Computer science; Natural language processing; Speech recognition; Artificial intelligence; Linguistics; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.001118946,0.00008639428,0.0001606616,0.0002139614,0.0001295809,0.0004340113,0.0003927999,0.00005620657,0.000003030725],"category_scores_gemma":[0.00006326967,0.00006929799,0.00004511684,0.0002182142,0.00006184983,0.0005184807,0.0002191059,0.0003124266,0.000004122754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001895149,"about_ca_system_score_gemma":0.0000396726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006684993,"about_ca_topic_score_gemma":9.388127e-7,"domain_scores_codex":[0.9990956,0.000168478,0.000359472,0.0001260245,0.0001473072,0.0001031584],"domain_scores_gemma":[0.9989322,0.000375735,0.0001625123,0.0002760005,0.0001862849,0.00006728626],"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":[0.000003531887,0.0000257267,0.0002492685,0.00004510889,0.00003565231,0.000008876251,0.001795964,0.000002042248,0.0007368337,0.0052845,0.001779226,0.9900333],"study_design_scores_gemma":[0.002653074,0.001794745,0.03991634,0.01168429,0.0002838229,0.01188082,0.001402766,0.4054271,0.02335966,0.3998957,0.09996752,0.001734163],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.266965,0.02013343,0.7006154,0.009754895,0.000252705,0.0001297888,8.149765e-7,0.00028433,0.001863602],"genre_scores_gemma":[0.8947037,0.002244836,0.1027211,0.0002099511,0.00006036591,8.55455e-7,7.356405e-7,0.000006888982,0.00005154485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9882991,"threshold_uncertainty_score":0.4185181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720329347241364,"score_gpt":0.282319251128827,"score_spread":0.2651159576564134,"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."}}