{"id":"W2222111835","doi":"","title":"The Application of Corpus in English Writing and Its Influences","year":2016,"lang":"en","type":"article","venue":"Studies in sociology of science","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Corpus linguistics; Computer science; Section (typography); Natural language processing; Strengths and weaknesses; Artificial intelligence; Text corpus; Linguistics; Psychology","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":[0.0203589,0.0003699684,0.000502507,0.003881201,0.00430048,0.008253955,0.001011329,0.0006992275,0.003907519],"category_scores_gemma":[0.1023754,0.0003718538,0.0002449754,0.006670758,0.007224982,0.005264492,0.004217932,0.001416664,0.0003639502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003569625,"about_ca_system_score_gemma":0.003849811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009251933,"about_ca_topic_score_gemma":0.008899502,"domain_scores_codex":[0.9502651,0.03974057,0.001658956,0.002379316,0.005316309,0.0006395832],"domain_scores_gemma":[0.7437687,0.2218246,0.01028262,0.007933604,0.01383723,0.002353299],"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":[0.0004540248,0.0003666167,0.2369802,0.001886411,0.0002308222,0.001741162,0.2199235,0.002139182,0.005748803,0.2212497,0.005212119,0.3040675],"study_design_scores_gemma":[0.0000831814,0.0007416111,0.4257767,0.003223607,0.0004508883,0.003032835,0.1522126,0.0125391,0.009292432,0.07666102,0.3157033,0.0002827335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.836788,0.01158947,0.02008367,0.00685832,0.0004803676,0.0002892227,0.0002787982,0.0001388091,0.1234933],"genre_scores_gemma":[0.9913652,0.001359935,0.004662085,0.0001962122,0.0001101502,0.00007374623,0.00006960054,0.00008519425,0.002077881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0203589,"threshold_uncertainty_score":0.1076695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03959051415692574,"score_gpt":0.4022037840373577,"score_spread":0.362613269880432,"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."}}