{"id":"W2113277595","doi":"10.3968/j.css.1923669720090504.004","title":"About some Characteristics of Black English","year":2009,"lang":"en","type":"article","venue":"Canadian social science","topic":"Linguistics, Language Diversity, and Identity","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Humanities; Variety (cybernetics); Political science; Art; Philosophy; 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":[0.001068559,0.0001079804,0.0001573771,0.001278084,0.003308282,0.002092975,0.0001808032,0.0003825234,0.003376999],"category_scores_gemma":[0.003463689,0.00008527719,0.00009242255,0.00152184,0.003241609,0.002233182,0.0007711499,0.0008710108,0.0002449025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001467069,"about_ca_system_score_gemma":0.0007209216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01897324,"about_ca_topic_score_gemma":0.02201567,"domain_scores_codex":[0.9993383,0.0002932055,0.00002637646,0.00009060284,0.0001276234,0.0001239319],"domain_scores_gemma":[0.998268,0.0007513603,0.0003686551,0.0000649822,0.0003508662,0.0001961557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001764868,0.00004550114,0.1128205,0.0001228315,0.00001943781,0.0007237539,0.5295731,0.0001742549,0.00297828,0.2981694,0.006812529,0.04838389],"study_design_scores_gemma":[0.00001744483,0.0001162484,0.2988028,0.0002544511,0.0000299805,0.001328133,0.427953,0.0005136573,0.001018732,0.08997627,0.1799104,0.00007894345],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9023022,0.001546611,0.001190759,0.008435792,0.00006660814,0.00001497182,0.0001839576,0.000008426175,0.08625067],"genre_scores_gemma":[0.9958482,0.0004051268,0.0002013507,0.0002229776,0.00003546998,0.000007435074,0.0000423128,0.000007860076,0.003229198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01897324,"threshold_uncertainty_score":0.03772557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529928791403522,"score_gpt":0.2163998740710652,"score_spread":0.20110058615703,"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."}}