{"id":"W4293072781","doi":"10.16995/dm.8073","title":"Illumination Detection in IIIF Medieval Manuscripts Using Deep Learning","year":2022,"lang":"en","type":"article","venue":"Digital Medievalist","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National de Physique Nucléaire et de Physique des Particules; Centre National de la Recherche Scientifique","keywords":"Computer science; Interoperability; Domain (mathematical analysis); Transfer of learning; Deep learning; Information retrieval; World Wide Web; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006050322,0.000157765,0.0001736367,0.000438748,0.0003163416,0.0002881004,0.000512649,0.00005154988,0.00003784968],"category_scores_gemma":[0.0002908689,0.0001837141,0.00007310151,0.0008071437,0.00006170423,0.001399313,0.0004726978,0.0004089906,0.00002035861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004425076,"about_ca_system_score_gemma":0.00003874193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005331105,"about_ca_topic_score_gemma":0.00004033625,"domain_scores_codex":[0.9980447,0.0001669952,0.0003432178,0.0004301422,0.0006906363,0.0003243398],"domain_scores_gemma":[0.9993529,0.00009671406,0.0001465224,0.0002367311,0.00009513609,0.00007201787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002310529,0.0001615294,0.0007560249,0.0000249087,0.00001232467,0.0001348918,0.001672208,0.0004138156,0.00545508,0.001123218,0.00005054495,0.9901723],"study_design_scores_gemma":[0.001977518,0.001098312,0.0046683,0.000121388,0.00002513615,0.0008019564,0.002681726,0.8680451,0.0528471,0.02157812,0.0446502,0.001505131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4643099,0.0002107828,0.5189829,0.0004323145,0.001430464,0.0005846017,0.00001553168,0.001052523,0.01298095],"genre_scores_gemma":[0.9966648,0.000007905298,0.002801029,0.0001272247,0.00007282569,0.00007820267,0.00003525099,0.00001924327,0.000193529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9886672,"threshold_uncertainty_score":0.7491644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112968539749353,"score_gpt":0.2525656625109896,"score_spread":0.2314359771134961,"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."}}