{"id":"W4307687269","doi":"10.5430/wjel.v12n8p382","title":"Learning Through Correction: Oral Corrective Feedback in Online EFL Interactions","year":2022,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Najran University","keywords":"Corrective feedback; Context (archaeology); Psychology; Sample (material); English as a foreign language; Mathematics education","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":[0.003743638,0.000528522,0.0004233991,0.0009533941,0.0009500748,0.002620405,0.0007586548,0.0007566668,0.003286177],"category_scores_gemma":[0.02855773,0.0001977787,0.0001993281,0.0006385174,0.001230102,0.002255008,0.001779376,0.0006803932,0.0005879657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006054196,"about_ca_system_score_gemma":0.001148047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001276958,"about_ca_topic_score_gemma":0.002361999,"domain_scores_codex":[0.9929674,0.004088485,0.00036371,0.0005812955,0.001610346,0.0003887737],"domain_scores_gemma":[0.9728732,0.0177521,0.004554558,0.0014786,0.002361373,0.0009800869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006742637,0.001087124,0.1205294,0.001439995,0.00004848802,0.002766502,0.1878674,0.0006426484,0.03505794,0.001487694,0.002533407,0.6458652],"study_design_scores_gemma":[0.000140872,0.003385888,0.5219424,0.002925556,0.0002808832,0.01244509,0.3093637,0.006561622,0.05023111,0.00586769,0.08646473,0.0003904456],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675148,0.0005142454,0.01596307,0.0005532211,0.00007951624,0.0001821944,0.00009140958,0.0002877295,0.01481376],"genre_scores_gemma":[0.987874,0.000279468,0.00840483,0.000125077,0.00002847248,0.00006831638,0.00004991127,0.00003761465,0.003132312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003743638,"threshold_uncertainty_score":0.01979846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183236092471986,"score_gpt":0.2791531417215241,"score_spread":0.2573207807968042,"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."}}