{"id":"W4387058119","doi":"10.33137/twpl.v45i1.41669","title":"Nominal linkers in Central Kurdish (Silemānī variety)","year":2023,"lang":"en","type":"article","venue":"Toronto Working Papers in Linguistics","topic":"Linguistics and Cultural Studies","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Definiteness; Noun phrase; Plural; Linguistics; Variety (cybernetics); Linker; Mathematics; Phrase; Computer science; Natural language processing; Artificial intelligence; Noun; Philosophy; Programming language","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0002515898,0.0002474981,0.0003181677,0.00006045377,0.0003569189,0.0001708042,0.0002327426,0.00008586201,0.0005641591],"category_scores_gemma":[0.001148718,0.0002274496,0.00009244771,0.00009563596,0.0001784357,0.00001760183,0.0001293801,0.0002564903,0.00005017736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003951959,"about_ca_system_score_gemma":0.00004087732,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006419729,"about_ca_topic_score_gemma":0.1211072,"domain_scores_codex":[0.9981702,0.00003408054,0.000442693,0.000334195,0.0002412694,0.0007775498],"domain_scores_gemma":[0.9993846,0.0001649805,0.00008908739,0.0001769456,0.00009966249,0.00008471835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009426763,0.0001627193,0.03337846,0.0001082766,0.0001008206,0.0003485726,0.1847573,0.0009723263,0.00001411018,0.7625024,0.006749266,0.01081151],"study_design_scores_gemma":[0.0004572658,0.00004650082,0.007759964,0.000192656,0.00002552568,3.771767e-7,0.01750512,0.0007887392,0.000001928936,0.001341738,0.9714988,0.0003813753],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.009616107,0.0008225927,0.000001107826,0.0001113727,0.008411805,0.0002260795,0.00002028195,0.0002147799,0.9805759],"genre_scores_gemma":[0.9881459,0.0002893316,0.0001848785,0.0001764432,0.005592624,0.00002403994,0.0000362815,0.00003383621,0.005516639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9785298,"threshold_uncertainty_score":0.9704751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03370660653897539,"score_gpt":0.2474455406044535,"score_spread":0.2137389340654781,"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."}}