{"id":"W4315866276","doi":"10.5430/wjel.v13n2p33","title":"The Textual Functions of Discourse Marker yalla in Jordanian Arabic","year":2023,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Language, Linguistics, Cultural Analysis","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Discourse marker; Conversation; Linguistics; Arabic; Computer science; Natural language processing; Psychology; Philosophy","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":[0.002017884,0.0003386814,0.0001891609,0.001785701,0.00165665,0.001934052,0.0003264056,0.0004094408,0.002267651],"category_scores_gemma":[0.007331851,0.0001765245,0.0001033476,0.001206516,0.001816706,0.002278036,0.001137813,0.0004237961,0.000477996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226319,"about_ca_system_score_gemma":0.0008402094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002020584,"about_ca_topic_score_gemma":0.002385402,"domain_scores_codex":[0.9978738,0.001405041,0.0001455917,0.0001864327,0.0002933574,0.00009578161],"domain_scores_gemma":[0.9924225,0.004338929,0.001443448,0.0003412072,0.001239782,0.0002141458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002026457,0.0001590565,0.1029653,0.001388687,0.00004385151,0.003407075,0.5540249,0.0008135676,0.1241343,0.03528085,0.002159682,0.1735963],"study_design_scores_gemma":[0.00005358263,0.0006787918,0.2361507,0.000935519,0.00008229416,0.004199885,0.5761926,0.009504317,0.05362641,0.007819355,0.1105784,0.0001782772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814637,0.0006025751,0.003834272,0.0003899226,0.00002702595,0.00005005483,0.0001798649,0.00005168533,0.01340085],"genre_scores_gemma":[0.9974689,0.0001177422,0.001485557,0.00001983528,0.00001051739,0.00002309062,0.00007802127,0.000009695873,0.0007865327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002267651,"threshold_uncertainty_score":0.01067173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326247983137693,"score_gpt":0.2468951921718886,"score_spread":0.2336327123405117,"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."}}