{"id":"W4394938787","doi":"10.5267/j.ijdns.2024.3.015","title":"Integrated multi-layer perceptron neural network and novel feature extraction for handwritten Arabic recognition","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Arabic; Artificial intelligence; Pattern recognition (psychology); Artificial neural network; Feature extraction; Perceptron; Layer (electronics); Feature (linguistics); Multilayer perceptron; Speech recognition; Natural language processing; Chemistry; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001783547,0.0001453501,0.0001676232,0.0002584686,0.0002051518,0.001268513,0.001360549,0.00007274849,0.000008857804],"category_scores_gemma":[0.0001532437,0.0001148868,0.00004816657,0.0004921102,0.0002009878,0.004824312,0.0004070032,0.0003387325,0.000002278767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006409904,"about_ca_system_score_gemma":0.0001589115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007760889,"about_ca_topic_score_gemma":0.00001649408,"domain_scores_codex":[0.9984016,0.00003738378,0.0003472432,0.0004666721,0.0004793381,0.0002677057],"domain_scores_gemma":[0.9985456,0.0002473569,0.0001943365,0.000214461,0.0006654389,0.0001327407],"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":[0.0000663333,0.000054288,0.0002649038,0.00001583778,0.00005846606,0.00002995435,0.0001597961,0.0001031481,0.01020147,0.001007837,0.01385112,0.9741868],"study_design_scores_gemma":[0.0007391282,0.0002795171,0.004538061,0.0007367948,0.0000469137,0.002140361,0.00006773796,0.9573744,0.0009290276,0.007032848,0.02582774,0.0002874835],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0231778,0.001344842,0.970342,0.002561313,0.002202769,0.0001694364,0.00008658333,0.00007650606,0.00003873637],"genre_scores_gemma":[0.5176321,0.0008740965,0.4793977,0.0004901586,0.001443061,0.000008519457,0.00007147248,0.00001189089,0.00007101698],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9738994,"threshold_uncertainty_score":0.9997683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06953866044816313,"score_gpt":0.3513299763094943,"score_spread":0.2817913158613311,"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."}}