{"id":"W2943818116","doi":"10.5539/mas.v13n5p88","title":"Arabic Text Classification: A Review","year":2019,"lang":"en","type":"review","venue":"Modern Applied Science","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Arabic; Weighting; Artificial intelligence; Classifier (UML); Decision tree; Natural language processing; Naive Bayes classifier; Support vector machine; Set (abstract data type); Data mining; Information retrieval; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001426114,0.0009556832,0.001126213,0.009377225,0.000739789,0.002564368,0.001668914,0.001059965,0.007461914],"category_scores_gemma":[0.005755672,0.0003646212,0.0008152401,0.008854106,0.0008086629,0.00460763,0.0006940776,0.001089602,0.00603976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008805445,"about_ca_system_score_gemma":0.001479277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002790734,"about_ca_topic_score_gemma":0.002627939,"domain_scores_codex":[0.9991779,0.000105197,0.0001544485,0.0001604414,0.0003585609,0.00004341445],"domain_scores_gemma":[0.9952214,0.002460669,0.0003445951,0.0001242837,0.001731392,0.0001175471],"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":[0.00003341746,0.00004159714,0.0005514341,0.004809873,0.00003213989,0.00006754653,0.00007119864,0.0002016249,0.0003820654,0.001282959,0.04130991,0.9512163],"study_design_scores_gemma":[0.0000131705,0.00009912159,0.004391262,0.00550977,0.0001429601,0.001417093,0.000363984,0.001654003,0.001754179,0.003779084,0.9808235,0.00005189379],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001589495,0.9751058,0.006538305,0.003323648,0.001753965,0.0001058186,0.0005355269,0.0002541476,0.01079331],"genre_scores_gemma":[0.009669708,0.9709648,0.008230756,0.001090458,0.002586032,0.000103955,0.001287316,0.00006329266,0.006003683],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009377225,"threshold_uncertainty_score":0.02496254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.126081744370099,"score_gpt":0.3611282266457068,"score_spread":0.2350464822756078,"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."}}