{"id":"W2982544864","doi":"10.5539/ijel.v9n6p257","title":"A Sociolinguistic Analysis of the Use of Arabizi in Social Media Among Saudi Arabians","year":2019,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Digital Communication and Language","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spelling; Phenomenon; Arabic; Compensation (psychology); Psychology; Code (set theory); Social phenomenon; Social media; Code-switching; Social psychology; Linguistics; Computer science; Sociology; Social science; World Wide Web","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0004018285,0.00008374213,0.0003020123,0.0004339785,0.00001767652,0.00007511966,0.00166725,0.00005648336,0.00002250108],"category_scores_gemma":[0.04674485,0.0000665418,0.0002880102,0.0005819327,0.0001078346,0.0001163394,0.0002462571,0.0002576498,7.803113e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007019257,"about_ca_system_score_gemma":0.0001222011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002923544,"about_ca_topic_score_gemma":0.0001257546,"domain_scores_codex":[0.9983461,0.00009693832,0.0007285357,0.00009482395,0.0006342026,0.00009939555],"domain_scores_gemma":[0.9900248,0.0008924775,0.0009197529,0.0003097241,0.007817897,0.00003533544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00009423238,0.0007720824,0.3073502,0.00003940866,0.002030122,0.00004129562,0.02660476,0.02288586,0.00007078165,0.6366975,0.001469669,0.001944075],"study_design_scores_gemma":[0.00205088,0.0001095232,0.8469754,0.0004073753,0.0004911444,0.000002344996,0.001159955,0.03044347,0.0005658686,0.008910409,0.1084437,0.0004399106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8988416,0.0001598314,0.00342161,0.0001122001,0.01038161,0.0001483106,0.0001066798,0.00002358644,0.08680462],"genre_scores_gemma":[0.9976161,0.00001523855,0.001774116,0.00008512563,0.000457581,3.729351e-7,0.000004400498,0.000005380148,0.00004174687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6277871,"threshold_uncertainty_score":0.9612848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03220584812825173,"score_gpt":0.2823508043437378,"score_spread":0.250144956215486,"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."}}