{"id":"W2140157922","doi":"10.1111/weng.12157","title":"Sentence‐final adverbs in Singapore English and Hong Kong English","year":2015,"lang":"en","type":"article","venue":"World Englishes","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Sentence; British English; English-based creole languages; History; Computer science; Modern language; Language assessment; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005675542,0.0002108746,0.000178405,0.000671298,0.0006512937,0.0007067813,0.0001798034,0.0001270587,0.004279056],"category_scores_gemma":[0.001471332,0.0001607348,0.00013147,0.001422071,0.0007987527,0.0006202926,0.0007253658,0.0002808462,0.0003542938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008246307,"about_ca_system_score_gemma":0.0005485642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05312818,"about_ca_topic_score_gemma":0.09734014,"domain_scores_codex":[0.9997146,0.00008063902,0.00004380585,0.00005845826,0.00004975132,0.00005271643],"domain_scores_gemma":[0.9986184,0.0005764583,0.000286778,0.00008953296,0.0003028157,0.0001260149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001545519,0.0002148363,0.6268404,0.0007186259,0.0003168691,0.005477789,0.2171026,0.0005140911,0.07460171,0.00715687,0.001881705,0.06362908],"study_design_scores_gemma":[0.00001746022,0.00008587473,0.9646994,0.0000380908,0.00005827473,0.0006946994,0.02651586,0.0004125889,0.002806056,0.0002833014,0.004363719,0.00002472437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996707,0.00007400478,0.00005024664,0.00002329323,0.000002535308,0.000004473422,0.0001395639,0.000002353653,0.002996562],"genre_scores_gemma":[0.9991031,0.00005058241,0.00005064777,0.000008979688,9.06413e-7,0.00000410411,0.0001562883,0.000004042386,0.000621448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05312818,"threshold_uncertainty_score":0.1056379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05031433929948378,"score_gpt":0.2976485398534406,"score_spread":0.2473342005539568,"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."}}