{"id":"W4235373705","doi":"10.32920/ryerson.14646426.v1","title":"Netspeak in China: features and impact on standard Chinese language","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Digital Communication and Language","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"","keywords":"China; Sovereignty; Chinese language; Standard Chinese; Standard language; Linguistics; Chinese people; Order (exchange); Sign (mathematics); History; Political science; Psychology; Sociology; Law; Politics; Economics; Mathematics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004397281,0.0002035795,0.0001495846,0.001041506,0.001382968,0.001187587,0.0003897694,0.0002028438,0.005906352],"category_scores_gemma":[0.001344673,0.0001117163,0.0001733817,0.002167372,0.00133035,0.00108698,0.001425922,0.0003973994,0.0002656983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002911284,"about_ca_system_score_gemma":0.002735822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.080692,"about_ca_topic_score_gemma":0.1184693,"domain_scores_codex":[0.9995839,0.00006423991,0.00002117878,0.00007439377,0.0001254484,0.0001308025],"domain_scores_gemma":[0.9988477,0.0001988273,0.0004006715,0.00006163529,0.0002143043,0.0002767452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000227431,0.0001301532,0.8916365,0.0002176585,0.00004533402,0.002931432,0.03613641,0.0006008128,0.002906603,0.008885389,0.002479004,0.05380328],"study_design_scores_gemma":[0.000009339236,0.00009746884,0.9531484,0.00004249016,0.00003015746,0.000374991,0.0357498,0.001187783,0.0009297486,0.001662868,0.006741208,0.00002572449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949764,0.00009302144,0.00004828849,0.0003180713,0.000004410767,0.000005441856,0.00008588609,0.000007283036,0.004461339],"genre_scores_gemma":[0.9983687,0.00008972279,0.00003090175,0.00002818859,0.000003328971,0.000003560476,0.00005693525,0.000003245229,0.001415402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.080692,"threshold_uncertainty_score":0.1604446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006915483373464101,"score_gpt":0.2977849659647856,"score_spread":0.2908694825913215,"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."}}