{"id":"W3099489575","doi":"10.31513/linguistica.2020.v16nesp.a39406","title":"Deriving coordinate nouns with Merge and Principles of efficient computation","year":2020,"lang":"pt","type":"article","venue":"Revista Linguíʃtica","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Merge (version control); Noun; Associative property; Computer science; Computation; Natural language processing; Linguistics; Mathematics; Artificial intelligence; Pure mathematics; Algorithm; Philosophy; Information retrieval","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":[0.002236056,0.0006304152,0.0006842929,0.002008442,0.001717767,0.004889861,0.001166125,0.001018735,0.005858161],"category_scores_gemma":[0.009138227,0.0005810864,0.001917735,0.001782121,0.005512528,0.01080864,0.003795384,0.001732949,0.001410413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564194,"about_ca_system_score_gemma":0.001312084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001975509,"about_ca_topic_score_gemma":0.002042888,"domain_scores_codex":[0.9974112,0.0008792183,0.00022455,0.0005064771,0.0007639474,0.0002145429],"domain_scores_gemma":[0.9965401,0.001631885,0.0003319079,0.0006953762,0.0006966095,0.0001041683],"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":[0.00002892815,0.00001270076,0.0009024131,0.00006499296,0.0000158649,0.0001620864,0.001760773,0.001944628,0.001532234,0.9688173,0.0004120389,0.02434612],"study_design_scores_gemma":[0.00001181893,0.0000399817,0.0006497756,0.00003403795,0.00002767242,0.0002991199,0.0006922834,0.01761166,0.005151659,0.9626614,0.01279427,0.00002622019],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0498879,0.000288648,0.9224691,0.0004460951,0.00004690954,0.00007537888,0.00008457192,0.0004144123,0.02628694],"genre_scores_gemma":[0.5631399,0.0004742829,0.4242139,0.0001763394,0.00009152864,0.0001902198,0.0002281695,0.0005665186,0.01091927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005858161,"threshold_uncertainty_score":0.01959747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0363172215559239,"score_gpt":0.2477146197074715,"score_spread":0.2113973981515476,"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."}}