{"id":"W6996572510","doi":"","title":"The semantics and syntax of Old English verbs of change of state: depriving, increasing, and learning","year":2021,"lang":"es","type":"other","venue":"RIUR (Universidad de La Rioja)","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Syntax; Semantics (computer science); Grammar; Mandarin Chinese; Simple past; Parsing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005050551,0.0002603959,0.0005607279,0.0002163523,0.0004290646,0.0001119917,0.0001727072,0.0001788335,0.0004618389],"category_scores_gemma":[0.0002207425,0.0002213924,0.0001517236,0.0001021547,0.001646465,0.00009862085,0.0002797314,0.0003846842,3.383766e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001630779,"about_ca_system_score_gemma":0.00004733077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005399425,"about_ca_topic_score_gemma":0.002785271,"domain_scores_codex":[0.9986078,0.000438609,0.0002329075,0.0002495215,0.000221185,0.0002499729],"domain_scores_gemma":[0.9980037,0.0009269908,0.0005710331,0.0002269986,0.0002148119,0.00005648933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002210658,0.0002128287,0.118431,0.005384912,0.002672032,0.0001322272,0.6997435,0.000002682046,0.0004516012,0.1589595,0.0009803986,0.01280822],"study_design_scores_gemma":[0.001620803,0.0004610316,0.1303048,0.005525822,0.001011496,0.00001879653,0.2779651,0.00006350155,0.0003117959,0.0003824406,0.5816329,0.0007014665],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.867196,0.03056576,0.000005572549,0.00004723107,0.0001287161,0.0001875892,0.0001160851,0.00002052164,0.1017325],"genre_scores_gemma":[0.9569169,0.02348846,0.0001144471,0.00001707902,0.0001896721,0.000002240338,0.000009900821,0.00006046757,0.01920084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5806525,"threshold_uncertainty_score":0.9028118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244707614560983,"score_gpt":0.2247864798817911,"score_spread":0.2123394037361813,"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."}}