{"id":"W4307356327","doi":"","title":"CREMMA Medieval Latin: Literary manuscript text recognition in Latin","year":2022,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Linguistics and language evolution","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medieval Latin; Latin Americans; Classics; History; Art; Literature; Linguistics; Philosophy","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":[0.001484388,0.0005146452,0.0002976124,0.002921109,0.001071357,0.004078884,0.0006572811,0.0005881612,0.01947924],"category_scores_gemma":[0.007430647,0.0002597435,0.0002415506,0.002585963,0.001102052,0.002615981,0.001876854,0.0004836019,0.009174095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043197,"about_ca_system_score_gemma":0.001682965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005758488,"about_ca_topic_score_gemma":0.005862526,"domain_scores_codex":[0.9988483,0.0004403604,0.000144502,0.0002920876,0.0001965784,0.00007805856],"domain_scores_gemma":[0.9959301,0.001327439,0.0004309281,0.0005833199,0.001491938,0.0002362498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008916038,0.0001908372,0.03048163,0.001496685,0.0000725983,0.001379657,0.01934848,0.001345043,0.07983267,0.02784707,0.0552326,0.781881],"study_design_scores_gemma":[0.0001109608,0.0002018414,0.06528678,0.0007485001,0.0001535853,0.003714829,0.02751703,0.03091364,0.08032228,0.01555193,0.7753371,0.0001415195],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5489914,0.009246906,0.1299057,0.01042625,0.002210124,0.0007133108,0.01023545,0.01783171,0.2704391],"genre_scores_gemma":[0.8407757,0.002197211,0.08331358,0.0003955664,0.0006350414,0.0002051774,0.01083608,0.00380952,0.05783221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01947924,"threshold_uncertainty_score":0.06516457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03654294151065691,"score_gpt":0.2295701121702896,"score_spread":0.1930271706596327,"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."}}