{"id":"W2969751580","doi":"","title":"The Right Marginal Notes on Glaídemain and Gúdemain in TCD MS 1337","year":2018,"lang":"en","type":"article","venue":"Studia Celtica Fennica","topic":"Linguistics and language evolution","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Margin (machine learning); Interpretation (philosophy); Literature; Battle; Philosophy; History; Linguistics; Art; Computer science; Ancient history","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":[0.001317744,0.0003269827,0.0003177941,0.002130576,0.005728704,0.003343201,0.0006021874,0.001084865,0.01549761],"category_scores_gemma":[0.004393968,0.0002082716,0.0001229943,0.002163257,0.005925901,0.002366731,0.002825485,0.002931378,0.002305931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007307498,"about_ca_system_score_gemma":0.002868577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09394297,"about_ca_topic_score_gemma":0.1389692,"domain_scores_codex":[0.9985008,0.0004643658,0.0001139145,0.0001653178,0.0005190208,0.0002366718],"domain_scores_gemma":[0.9982784,0.0009082243,0.0001554704,0.0001207037,0.0004449714,0.00009236941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001477621,0.00001488255,0.001811426,0.0003449606,0.000005956805,0.001366447,0.131413,0.00007351342,0.002582995,0.5594805,0.2568569,0.04590173],"study_design_scores_gemma":[0.000003286559,0.000007465944,0.001824073,0.0001674506,0.000002387575,0.0001719616,0.01616124,0.00002678343,0.0005318032,0.003000497,0.9780917,0.00001133846],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09617809,0.01509916,0.004747331,0.0358948,0.004412694,0.00009130648,0.001738057,0.0002672613,0.8415713],"genre_scores_gemma":[0.7970334,0.0041975,0.002585171,0.008643817,0.001317773,0.00008786877,0.00137437,0.0007648393,0.1839953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09394297,"threshold_uncertainty_score":0.1867923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517018083688294,"score_gpt":0.2428065515993264,"score_spread":0.2276363707624435,"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."}}