{"id":"W4387058249","doi":"10.33137/twpl.v45i1.41689","title":"Nominal linkers in Gilaki","year":2023,"lang":"en","type":"article","venue":"Toronto Working Papers in Linguistics","topic":"Linguistics and language evolution","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Attributive; Noun phrase; Possessive; Head (geology); Variety (cybernetics); Specifier; Linguistics; Complement (music); Phrase; Noun; Computer science; Natural language processing; Nominalization; Genitive case; Artificial intelligence; Mathematics; Philosophy; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003769653,0.0002403611,0.0003877227,0.001555928,0.002751233,0.001555869,0.0004360481,0.0003352958,0.007970043],"category_scores_gemma":[0.0005382634,0.000195014,0.0001781829,0.002540318,0.002605961,0.001592687,0.002027781,0.0008685762,0.001123515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002274019,"about_ca_system_score_gemma":0.0009095183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006185605,"about_ca_topic_score_gemma":0.01524614,"domain_scores_codex":[0.9996226,0.00004722404,0.00002532551,0.00009531916,0.0001069699,0.0001024572],"domain_scores_gemma":[0.9997985,0.00004104765,0.00006097178,0.00003201773,0.00004043644,0.00002707245],"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":[0.0008412451,0.0001521665,0.05894151,0.0007178731,0.00005302568,0.01073545,0.11935,0.0006107446,0.03983482,0.6224984,0.008886891,0.1373778],"study_design_scores_gemma":[0.0001648078,0.0002378194,0.1472822,0.0001956906,0.00009437959,0.008595974,0.059071,0.0007250841,0.007351762,0.04581213,0.7303482,0.0001209398],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8072206,0.00157343,0.002665772,0.0005797666,0.0001397621,0.00004687901,0.0005211566,0.0002199285,0.1870327],"genre_scores_gemma":[0.9880505,0.0003133762,0.00147102,0.00008385906,0.00003593117,0.00001996429,0.0004436299,0.0000857026,0.009496041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007970043,"threshold_uncertainty_score":0.02666241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856765090228822,"score_gpt":0.2556205723239094,"score_spread":0.2270529214216212,"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."}}