{"id":"W3172079241","doi":"","title":"The lemmatisation of Old English comparative adverbs.","year":2020,"lang":"es","type":"article","venue":"RAEL: revista electrónica de lingüística aplicada","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Lemma (botany); Humanities; Poetry; Artificial intelligence; Lexicography; Natural language processing; History; Computer science; Art; Philosophy","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":[0.002286883,0.0003481551,0.0003705155,0.003384119,0.001457617,0.00232163,0.0004510437,0.0002964069,0.007018552],"category_scores_gemma":[0.00949579,0.000351412,0.0003573689,0.002620929,0.00197528,0.001884681,0.001837607,0.0008630505,0.001598085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115291,"about_ca_system_score_gemma":0.0009993664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002454712,"about_ca_topic_score_gemma":0.006145555,"domain_scores_codex":[0.9978459,0.0009642649,0.0002799827,0.0003845175,0.0004337603,0.0000915116],"domain_scores_gemma":[0.9886211,0.0076963,0.0007812677,0.001283562,0.001510298,0.0001074816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009421005,0.0001714928,0.0360255,0.004008706,0.0000909288,0.004116137,0.1285258,0.001404195,0.2435404,0.09851736,0.01360214,0.4690553],"study_design_scores_gemma":[0.00009999367,0.0003710591,0.1537244,0.0009820361,0.0001673581,0.006440098,0.06142516,0.0164882,0.2949031,0.02295266,0.4422791,0.000166782],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7516381,0.003105147,0.1805503,0.0008507887,0.0004179802,0.001282867,0.00485197,0.001271333,0.05603151],"genre_scores_gemma":[0.8940122,0.0006709571,0.09361516,0.0001158462,0.00006868946,0.0003712038,0.003393288,0.0004982068,0.007254537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007018552,"threshold_uncertainty_score":0.02347946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02536193955316517,"score_gpt":0.2587672251489737,"score_spread":0.2334052855958085,"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."}}