{"id":"W2148386031","doi":"10.1162/ling.2006.37.2.329","title":"Raising to Object in Japanese: A Small Clause Analysis","year":2006,"lang":"en","type":"article","venue":"Linguistic Inquiry","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Icon; Citation; Download; Computer science; Object (grammar); Raising (metalworking); Linguistics; Information retrieval; Library science; Filter (signal processing); World Wide Web; Artificial intelligence; Mathematics; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00138374,0.0008282702,0.0006150435,0.001637897,0.002911699,0.003499502,0.0008597669,0.001082625,0.01411659],"category_scores_gemma":[0.002798475,0.0009133705,0.0005917636,0.001620091,0.003760889,0.004896597,0.002548076,0.002025566,0.0009974284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002522573,"about_ca_system_score_gemma":0.00109505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01705839,"about_ca_topic_score_gemma":0.02130889,"domain_scores_codex":[0.9991565,0.0003421968,0.00007390257,0.0001629931,0.0001710011,0.0000934184],"domain_scores_gemma":[0.9985947,0.0007531173,0.0001116322,0.0001346216,0.0003394158,0.00006653392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005289663,0.0001139582,0.01175103,0.0008476783,0.00008561142,0.003481079,0.0945467,0.000797963,0.01336115,0.7765701,0.02385657,0.07405908],"study_design_scores_gemma":[0.00027292,0.0004847411,0.1092516,0.0009135152,0.0009477457,0.005626086,0.09192315,0.02300171,0.02492985,0.4300276,0.3122038,0.0004173699],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3970146,0.006271522,0.09448148,0.006542777,0.0005647667,0.000270561,0.001591199,0.0008950855,0.492368],"genre_scores_gemma":[0.9710307,0.0008237065,0.01043309,0.0003808444,0.0001675836,0.00007379233,0.0006718131,0.0005724337,0.01584599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01705839,"threshold_uncertainty_score":0.0472247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05999699038156184,"score_gpt":0.2845633775433342,"score_spread":0.2245663871617724,"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."}}