{"id":"W2907111026","doi":"10.5539/ijel.v9n1p301","title":"Arabizi Among Kuwaiti Youths: Reshaping the Standard Arabic Orthography","year":2018,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Digital Communication and Language","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Code-switching; Style (visual arts); Psychology; Code-mixing; Point (geometry); Arabic; Transliteration; Linguistics; Computer science; Geography; Artificial intelligence","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":[0.0006616183,0.0003545455,0.0001948308,0.0006450551,0.00252949,0.001764818,0.0003748803,0.0005713002,0.002223162],"category_scores_gemma":[0.001039349,0.0002716828,0.0001927513,0.0005176525,0.001391934,0.0009112352,0.00109542,0.0007387681,0.0005855039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006249067,"about_ca_system_score_gemma":0.0007532724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01982358,"about_ca_topic_score_gemma":0.05285963,"domain_scores_codex":[0.9997347,0.00008440499,0.00001734477,0.00003310328,0.00004727846,0.00008301783],"domain_scores_gemma":[0.9996384,0.00008391348,0.0001074936,0.00002633835,0.00006962386,0.00007423298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00009462324,0.0001485449,0.2082735,0.0001904589,0.00001185987,0.004201524,0.7438193,0.00002135048,0.01044867,0.0009673086,0.000651842,0.03117103],"study_design_scores_gemma":[0.000004566221,0.0001586043,0.1993303,0.0001326658,0.00002577297,0.002679732,0.7865831,0.0001099276,0.001392375,0.0001456855,0.009415813,0.00002151403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985305,0.0001035463,0.00003834076,0.0000948715,0.000007758305,0.000008492972,0.000009649071,0.000002855373,0.001204012],"genre_scores_gemma":[0.9980571,0.0002897662,0.0001726253,0.0000816879,0.000005147676,0.000008606541,0.00001771784,0.000003222882,0.001364257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01982358,"threshold_uncertainty_score":0.03941637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738525237197866,"score_gpt":0.2797088910527195,"score_spread":0.2623236386807408,"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."}}