{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002142088,0.0002489566,0.0003067021,0.0001666325,0.00003119158,0.0009320301,0.001031497,0.0001235678,0.00008512673],"category_scores_gemma":[0.00006899101,0.0001690844,0.0001030597,0.0002343079,0.00002718869,0.0002274921,0.002293261,0.0006005574,0.000005599996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007050201,"about_ca_system_score_gemma":0.0001061465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008349723,"about_ca_topic_score_gemma":0.0009260858,"domain_scores_codex":[0.9988729,0.0001027497,0.0001756744,0.0004276776,0.000232821,0.0001881539],"domain_scores_gemma":[0.9983259,0.00007082886,0.00006832809,0.001413894,0.00002430667,0.00009672462],"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":[0.0003460589,0.001520055,0.02785212,0.0006392889,0.0004406356,0.002335747,0.09935409,0.005656861,0.001039236,0.1669288,0.01231304,0.6815741],"study_design_scores_gemma":[0.0008031595,0.0001775643,0.9896446,0.0003217614,0.000004878043,0.00005044735,0.0006422748,0.003797559,0.0002603699,0.002861076,0.0006719653,0.0007643751],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.764361,0.00277204,0.001672887,0.00101741,0.00009174877,0.000174397,0.00001951273,0.00016255,0.2297284],"genre_scores_gemma":[0.9943361,0.0001146097,0.003860455,0.0004934968,0.00001772155,0.000008622395,0.00004356315,0.00001134615,0.001114069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9617925,"threshold_uncertainty_score":0.8987588,"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."}}