{"id":"W6976673881","doi":"10.60692/hwq4j-m3d14","title":"Classifying Arabic Text Using KNN Classifier","year":2016,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Classifier (UML); Search engine indexing; Pattern recognition (psychology); Feature selection; Word error rate; Term (time)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008990754,0.001103152,0.0009116099,0.005728563,0.001210448,0.00163991,0.0009818143,0.001313706,0.00475838],"category_scores_gemma":[0.002836762,0.0001894143,0.0006909645,0.002917617,0.0003813893,0.00134858,0.0004739883,0.0007384768,0.00487769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009217673,"about_ca_system_score_gemma":0.001053354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00896313,"about_ca_topic_score_gemma":0.008519637,"domain_scores_codex":[0.9986941,0.0001308217,0.0002085916,0.0002983498,0.0005302322,0.0001378267],"domain_scores_gemma":[0.9984363,0.0003934783,0.0001048459,0.00009043478,0.0009171252,0.00005791315],"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":[0.0005136314,0.0003223711,0.008220012,0.0004901526,0.00010678,0.0005264616,0.0003182903,0.01557834,0.02365303,0.00143448,0.02021764,0.9286188],"study_design_scores_gemma":[0.00006697456,0.000466729,0.01990031,0.0002864836,0.0001564804,0.001363082,0.001451758,0.8630739,0.0597261,0.005731737,0.04763094,0.0001455023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4504531,0.006358316,0.4648755,0.001711111,0.002114091,0.002549934,0.008613166,0.01654562,0.04677919],"genre_scores_gemma":[0.5362718,0.002103594,0.4238173,0.0003459527,0.0003918659,0.0006304237,0.009521756,0.0002155554,0.0267018],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00896313,"threshold_uncertainty_score":0.01782191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07232163768643263,"score_gpt":0.2359401238020931,"score_spread":0.1636184861156604,"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."}}