{"id":"W4390056983","doi":"10.33137/twpl.v46i1.39252","title":"What's in a copula?","year":2023,"lang":"en","type":"article","venue":"Toronto Working Papers in Linguistics","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Copula (linguistics); Morpheme; Linguistics; Contrast (vision); Mathematics; Invariant (physics); Semantic property; Range (aeronautics); Computer science; Philosophy; Artificial intelligence","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":[0.001946969,0.000414387,0.0005690676,0.0009121457,0.003392081,0.003588291,0.001000943,0.001002489,0.01078927],"category_scores_gemma":[0.005048958,0.0003188566,0.0005304769,0.001140273,0.005547907,0.008064497,0.002492674,0.00155769,0.001792661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002523448,"about_ca_system_score_gemma":0.001474153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009166863,"about_ca_topic_score_gemma":0.005757443,"domain_scores_codex":[0.9986304,0.0003689782,0.00006736956,0.0004050826,0.0002905851,0.0002376171],"domain_scores_gemma":[0.9985102,0.0005660646,0.0001666433,0.0002463514,0.0003687201,0.0001420276],"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":[0.00005519268,0.00002503208,0.002905119,0.00008928113,0.0000454233,0.001114252,0.0135856,0.00009546741,0.001961909,0.9464792,0.009141468,0.02450202],"study_design_scores_gemma":[0.00002806891,0.00005542533,0.008909093,0.0002367408,0.00009044507,0.004206807,0.02633943,0.001543801,0.003849877,0.5795467,0.3750875,0.00010603],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.244564,0.007237053,0.1006944,0.03122837,0.002525607,0.0001540066,0.0006621207,0.0008369667,0.6120974],"genre_scores_gemma":[0.9780973,0.0009090834,0.004986362,0.001842698,0.0002952814,0.00003271853,0.0001901924,0.0002829985,0.01336352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01078927,"threshold_uncertainty_score":0.03609371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03814806290153441,"score_gpt":0.2696302230825946,"score_spread":0.2314821601810602,"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."}}