{"id":"W2312144670","doi":"10.5430/elr.v5n1p32","title":"Exploring Salient Socio-Linguistic Features of African-American English Vernacular","year":2016,"lang":"en","type":"article","venue":"English Linguistics Research","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vernacular; Variety (cybernetics); American English; Linguistics; Salient; History; Varieties of English; Sociology; Psychology; Computer science; Artificial intelligence","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":[0.0005557484,0.0001363639,0.0001419328,0.0008285894,0.001277631,0.001177627,0.000188988,0.000199288,0.001396891],"category_scores_gemma":[0.001827582,0.0001018122,0.00008529898,0.0005753948,0.0007989313,0.0008584089,0.0008212258,0.0002701804,0.0001349042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003208793,"about_ca_system_score_gemma":0.0003462087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004873953,"about_ca_topic_score_gemma":0.01789714,"domain_scores_codex":[0.9997005,0.0001198596,0.00002014659,0.00003992333,0.00005346756,0.00006610288],"domain_scores_gemma":[0.9992492,0.000234411,0.0002685394,0.00002879198,0.0001309536,0.00008818164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009616326,0.0001304239,0.5343001,0.0001400708,0.00002143817,0.001573834,0.4119363,0.00003145004,0.01388561,0.002718505,0.0004097392,0.03475645],"study_design_scores_gemma":[0.000001625357,0.00006397902,0.6135974,0.0000606757,0.000007413592,0.0004875346,0.3806771,0.00009176754,0.0005512428,0.000333168,0.00411828,0.000009807926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985318,0.00006421754,0.00006793956,0.00005750294,0.000002857698,0.000003468774,0.00001065948,4.87815e-7,0.001261023],"genre_scores_gemma":[0.9995165,0.00009752802,0.000111435,0.00002411818,0.000003742244,0.000005897245,0.00001888099,0.000001077262,0.0002208571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004873953,"threshold_uncertainty_score":0.009691179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1442199807774336,"score_gpt":0.3959984076747544,"score_spread":0.2517784268973208,"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."}}