{"id":"W7074138026","doi":"","title":"The Semantics of Evaluational Adjectives: Perspectives from Natural Semantic Metalanguage and Appraisal","year":2017,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Nuclear Structure and Function","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Metalanguage; Semantics (computer science); Subjectivity; Relevance (law); Identification (biology); Natural language; Semantic analysis (machine learning)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006716623,0.00008821148,0.00008688043,0.00002858869,0.0003563013,0.00003469943,0.000207453,0.0000700501,0.00002497774],"category_scores_gemma":[0.0001429761,0.00007274591,0.00006071595,0.00003531135,0.0002703322,0.00001557644,0.0001605308,0.00008049964,0.000002653929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009551746,"about_ca_system_score_gemma":0.00002523208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001316432,"about_ca_topic_score_gemma":0.005263296,"domain_scores_codex":[0.9994832,0.00004817186,0.00005836917,0.0002085389,0.0001079701,0.00009370458],"domain_scores_gemma":[0.9994351,0.0000365124,0.000103043,0.0003155086,0.00007970534,0.00003015751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00147912,0.0001282265,0.8885843,0.00003410695,0.001401553,0.00004110478,0.000585963,0.00005624286,0.07494571,0.008041047,0.01072452,0.0139781],"study_design_scores_gemma":[0.003755378,0.0005186248,0.6734691,0.00003998477,0.000627643,1.670336e-7,0.09349494,0.001192809,0.06746712,0.001252499,0.157466,0.0007157632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969439,0.0005790105,0.0001753375,0.0001582594,0.0002077064,0.00007173303,0.00002266364,0.000005452305,0.001835918],"genre_scores_gemma":[0.9987419,0.0001513075,0.0001912991,0.00001173836,0.0001103057,1.632843e-7,0.00002747951,0.000007623142,0.0007582216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2151152,"threshold_uncertainty_score":0.2966492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007621591428721964,"score_gpt":0.2382268179011611,"score_spread":0.2306052264724392,"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."}}