{"id":"W2781419951","doi":"10.5539/ijel.v8n2p288","title":"Concord in English and Arabic: A Contrastive Study","year":2017,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Swearing, Euphemism, Multilingualism","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Phenomenon; Sentence; Arabic; Contrastive analysis; Grammar; Computer science; Natural language processing; Psychology; Artificial intelligence; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001713785,0.0001232731,0.0002728875,0.0001653654,0.0002408042,0.0005024295,0.0009081344,0.00009444157,0.00003765242],"category_scores_gemma":[0.4240178,0.0001253236,0.00006440337,0.00004156999,0.0003446945,0.0001873462,0.0001418898,0.0004363874,0.000001213587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001979997,"about_ca_system_score_gemma":0.0003123321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009926145,"about_ca_topic_score_gemma":0.001889304,"domain_scores_codex":[0.9981529,0.0001204268,0.0005517326,0.0001720913,0.0007877247,0.0002150943],"domain_scores_gemma":[0.9778965,0.0006102838,0.0008156782,0.0001596724,0.02036237,0.0001555366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003237946,0.0006614182,0.7381806,0.000006259526,0.0003000579,0.0008073455,0.23774,0.00005422723,0.000009755337,0.01604468,0.001173469,0.004698303],"study_design_scores_gemma":[0.009660525,0.0004293463,0.3032739,0.0003812744,0.0001340977,0.000003785771,0.1245337,0.0001753378,0.0001896639,0.005468466,0.55516,0.0005898318],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8753316,0.0001172032,0.00002495802,0.00004973595,0.02461833,0.0001782487,0.00001208467,0.00002399881,0.09964386],"genre_scores_gemma":[0.979714,0.00009810441,0.0003974254,0.00006289279,0.01955389,0.000002036909,7.015852e-7,0.00001319103,0.0001577184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5539866,"threshold_uncertainty_score":0.5808339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0323240816563594,"score_gpt":0.3808003650209835,"score_spread":0.3484762833646241,"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."}}