{"id":"W1502552837","doi":"10.1017/cbo9780511663659","title":"Morpheme order and semantic scope word formation in the Athapaskan verb","year":2000,"lang":"en","type":"book","venue":"","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":295,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Lexicon; Affix; Linguistics; Verb; Morpheme; Lexical item; Word order; Computer science; Natural language processing; Scope (computer science); Word formation; Artificial intelligence; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0002962973,0.0001773766,0.0001543063,0.0006901033,0.001229057,0.002411436,0.0003226336,0.0004554175,0.00216745],"category_scores_gemma":[0.0006425992,0.0001909826,0.0001419776,0.001146578,0.004132898,0.003759578,0.0008698774,0.0009715627,0.0002523202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008395487,"about_ca_system_score_gemma":0.0004750168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001587745,"about_ca_topic_score_gemma":0.002494436,"domain_scores_codex":[0.9998034,0.0000863388,0.00001090814,0.00003755417,0.00004126674,0.0000205581],"domain_scores_gemma":[0.9997615,0.0001539138,0.00002328459,0.00002325591,0.00002947284,0.000008599717],"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":[0.00003039302,0.000008829081,0.001256818,0.0000398698,0.000004661841,0.0001408023,0.01151955,0.0001734924,0.001706486,0.9684435,0.0009230103,0.01575272],"study_design_scores_gemma":[0.00002341617,0.00007671601,0.0183419,0.0001207375,0.0000256794,0.0009468895,0.01679141,0.001808807,0.002832244,0.8375855,0.1214189,0.00002784178],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.4590385,0.003934519,0.02138663,0.001614756,0.0001201635,0.00004244143,0.0002209891,0.00005794504,0.5135841],"genre_scores_gemma":[0.9794468,0.001148953,0.003539172,0.00008641278,0.00003824055,0.00003239157,0.0001255502,0.00004522146,0.01553731],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.002411436,"threshold_uncertainty_score":0.007250905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02538826960341489,"score_gpt":0.2235124850323428,"score_spread":0.1981242154289279,"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."}}