{"id":"W2040976585","doi":"10.5539/ass.v5n2p84","title":"Accuracy & Fluency – Inspiration from Error-correction of Interlanguage Theory","year":2009,"lang":"en","type":"article","venue":"Asian Social Science","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interlanguage; Fluency; Relation (database); Linguistics; Value (mathematics); Computer science; Psychology; Cognitive psychology; Artificial intelligence; Mathematics education; Philosophy; Machine learning","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":[0.005028047,0.0006304735,0.0006401523,0.00382508,0.001043385,0.00380587,0.00185975,0.001603995,0.00243896],"category_scores_gemma":[0.01924817,0.0002496963,0.0007271421,0.002206095,0.01458121,0.005903659,0.002174194,0.002331601,0.0006742271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002563305,"about_ca_system_score_gemma":0.001415488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002427851,"about_ca_topic_score_gemma":0.000938208,"domain_scores_codex":[0.9941414,0.002226066,0.000598434,0.0008559632,0.001906457,0.000271563],"domain_scores_gemma":[0.9755934,0.01703137,0.001715226,0.002144826,0.003214292,0.0003008595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002863935,0.00003191366,0.002263825,0.0001886714,0.00002747616,0.0002684456,0.003724581,0.002447575,0.0003417532,0.9031317,0.002504927,0.08504054],"study_design_scores_gemma":[0.00001144778,0.00004505302,0.001850794,0.0001673553,0.00001989028,0.0004824863,0.0004700087,0.006121436,0.001075045,0.9626037,0.02711432,0.00003831511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04725658,0.01918875,0.6464694,0.01725816,0.001176742,0.0001205547,0.0003398498,0.0007836843,0.2674062],"genre_scores_gemma":[0.88602,0.005418964,0.0862596,0.001420239,0.0008338533,0.0002026472,0.0001390468,0.0003006246,0.0194049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005028047,"threshold_uncertainty_score":0.02659118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697759009666122,"score_gpt":0.2995111639648365,"score_spread":0.2725335738681752,"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."}}