{"id":"W4323314848","doi":"10.5430/wjel.v13n2p450","title":"Code Choices in Marriage Discourse Preach: A Sociolinguistic Analysis","year":2023,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Linguistics and Language Analysis","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indonesian; Linguistics; Arabic; Code-mixing; Phrase; Computer science; Meaning (existential); Narrative; Code (set theory); Code-switching; Phenomenon; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000972417,0.0001805705,0.0005586643,0.001878065,0.0001204842,0.0002316888,0.0003539507,0.00003602386,0.002920569],"category_scores_gemma":[0.002278708,0.0001422468,0.0004778564,0.0008944139,0.0001254371,0.0001291219,0.0000566089,0.0003670925,0.00002911964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005563935,"about_ca_system_score_gemma":0.00004565882,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005821981,"about_ca_topic_score_gemma":0.02844326,"domain_scores_codex":[0.9983216,0.0001018802,0.0006677698,0.0001835674,0.0003848475,0.0003403513],"domain_scores_gemma":[0.9984436,0.000300532,0.0004141582,0.0002557324,0.0004672288,0.0001187707],"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":[0.0000871227,0.0003251933,0.01714159,0.0001044874,0.003011852,0.003737781,0.9209556,0.002041187,0.00004787888,0.03979092,0.009958643,0.002797731],"study_design_scores_gemma":[0.002864225,0.0001866481,0.008302144,0.0004058286,0.00654152,0.000004949582,0.3626721,0.003811244,0.00009823956,0.001970456,0.6119527,0.001190018],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8390548,0.002570251,0.00002245101,0.0001563815,0.002096291,0.0001185277,0.0001711444,0.000108735,0.1557014],"genre_scores_gemma":[0.97959,0.00005878478,0.00006920709,0.0001220469,0.006006413,0.000003637132,0.00005190323,0.00002563231,0.01407237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.601994,"threshold_uncertainty_score":0.9979909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194618560480355,"score_gpt":0.2875024678100424,"score_spread":0.2680406117620069,"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."}}