{"id":"W1817902173","doi":"","title":"Language Attrition for Chinese Engineering Freshmen in Chinese Context","year":2015,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Attrition; Context (archaeology); Phenomenon; English language; Mathematics education; Order (exchange); Psychology; Linguistics; History; Epistemology","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":[0.001136061,0.0002642306,0.0004045972,0.00135962,0.006562791,0.001769585,0.0007843165,0.0006707838,0.005195403],"category_scores_gemma":[0.002553093,0.0001842039,0.0004334391,0.001439421,0.001016377,0.001533681,0.002786631,0.001306596,0.000409593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002936233,"about_ca_system_score_gemma":0.006610102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08093131,"about_ca_topic_score_gemma":0.1351584,"domain_scores_codex":[0.9985461,0.0001557641,0.0000773451,0.0001098072,0.0002422863,0.0008687651],"domain_scores_gemma":[0.997986,0.0002069629,0.0005319568,0.00005807957,0.0003384073,0.0008787272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000119154,0.0003062157,0.8728132,0.0001078444,0.00001884691,0.002362375,0.095348,0.00006629059,0.0005430325,0.0009303224,0.001682398,0.02570235],"study_design_scores_gemma":[0.000007721461,0.0002109,0.7365472,0.0001126728,0.00002720462,0.00057189,0.2567035,0.0003578182,0.000281312,0.0003888167,0.004754757,0.00003620966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985341,0.0001187773,0.00002514074,0.0005575513,0.000009529699,0.000007286639,0.00002085775,0.000001483392,0.0007254218],"genre_scores_gemma":[0.998001,0.0001843798,0.00003122306,0.0001626294,0.000009888352,0.00001262231,0.00004365918,0.000001953284,0.001552717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08093131,"threshold_uncertainty_score":0.1609204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02821087353327274,"score_gpt":0.304838460053272,"score_spread":0.2766275865199992,"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."}}