{"id":"W1598903884","doi":"10.1007/978-3-642-03767-2_20","title":"A New Approach for Segmentation and Recognition of Arabic Handwritten Touching Numeral Pairs","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Numeral system; Computer science; Artificial intelligence; Pattern recognition (psychology); Arabic numerals; Segmentation; Speech recognition; Set (abstract data type); Image segmentation; Arabic; Connected component; Linguistics","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"],"consensus_categories":[],"category_scores_codex":[0.0008461832,0.0003872867,0.0005007511,0.0008151782,0.0001594058,0.0003532334,0.001030407,0.0002812799,0.00001171583],"category_scores_gemma":[0.00007901237,0.0003767488,0.0001249208,0.0003639008,0.0002227624,0.0008424059,0.000285779,0.0003794292,0.000003417283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001396413,"about_ca_system_score_gemma":0.0002935343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003466053,"about_ca_topic_score_gemma":0.00001366608,"domain_scores_codex":[0.9972965,0.00003747065,0.0005577804,0.001164473,0.0005500766,0.0003937686],"domain_scores_gemma":[0.9983646,0.0003002603,0.0003821178,0.0005339612,0.0002722676,0.0001468014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009450496,0.00001995955,0.000007287666,0.00006722329,0.000007954898,0.000002727564,0.0005296312,0.0002177186,0.000645883,0.0008550572,0.00004461316,0.9975925],"study_design_scores_gemma":[0.0009414713,0.0006575586,0.00007884522,0.0007960034,0.00003298182,0.0001139515,0.000001007031,0.2654552,0.0375479,0.6932722,0.0002011299,0.0009017274],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008721984,0.0002032128,0.9965875,0.0002709561,0.0002082683,0.0009444466,0.00001065595,0.0001776618,0.001510123],"genre_scores_gemma":[0.01067514,0.00006410263,0.9881151,0.0006157072,0.0002254966,0.00002673399,0.00003710093,0.00002221266,0.0002184502],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9966908,"threshold_uncertainty_score":0.9998685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452815774154836,"score_gpt":0.2580449394556602,"score_spread":0.2335167817141119,"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."}}