{"id":"W2405542986","doi":"10.5072/zenodo.243942","title":"A Comparative Survey of Image Binarisation Algorithms for Optical Recognition on Degraded Musical Sources.","year":2007,"lang":"en","type":"article","venue":"Bern Open Repository and Information System (University of Bern)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Preprocessor; Grayscale; Artificial intelligence; Musical; Set (abstract data type); Image (mathematics); Visual arts","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011043,0.0000824312,0.0002410451,0.0001242572,0.0002847149,0.0001278158,0.0003286351,0.00007503406,0.000001974065],"category_scores_gemma":[0.0000145179,0.00008744276,0.00004047355,0.0001991816,0.00008767303,0.003075862,0.0001403899,0.00005971128,0.000006133487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004808286,"about_ca_system_score_gemma":0.00006076591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004707644,"about_ca_topic_score_gemma":0.00001638221,"domain_scores_codex":[0.9991799,0.00006430251,0.0003001694,0.0001397265,0.0002098017,0.0001061191],"domain_scores_gemma":[0.9987179,0.000170484,0.0004882486,0.0001475766,0.000411463,0.0000643457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007501784,0.001217515,0.01735347,0.005481655,0.0008014266,0.00005378298,0.2246617,0.0003855496,0.01499093,0.08538992,0.00730836,0.6348539],"study_design_scores_gemma":[0.008793117,0.001671715,0.6837547,0.001561166,0.0001397667,0.0001706884,0.03689751,0.1981159,0.06502194,0.0001814855,0.002663538,0.001028451],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4546965,0.000004372097,0.5357283,0.00004110064,0.00009100355,0.0003154724,0.00001700389,0.0000200078,0.00908624],"genre_scores_gemma":[0.9720538,8.337173e-7,0.02776298,0.00003285635,0.00001343536,7.357641e-7,0.00004340931,0.000001798023,0.00009013792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6664012,"threshold_uncertainty_score":0.3565812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06177932309183542,"score_gpt":0.2608215928808873,"score_spread":0.1990422697890519,"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."}}