{"id":"W2092619501","doi":"10.1007/s10044-007-0094-6","title":"Ensemble of HMM classifiers based on the clustering validity index for a handwritten numeral recognizer","year":2007,"lang":"en","type":"article","venue":"Pattern Analysis and Applications","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hidden Markov model; Codebook; Pattern recognition (psychology); Computer science; Vector quantization; Artificial intelligence; Cluster analysis; Linde–Buzo–Gray algorithm; Speech recognition","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002510896,0.000719206,0.001875639,0.001524204,0.0008834128,0.001229134,0.001118791,0.001290995,0.001353078],"category_scores_gemma":[0.004331183,0.0005181768,0.0009930355,0.0009167609,0.0002479628,0.00155785,0.0007739186,0.001090072,0.00109445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007622249,"about_ca_system_score_gemma":0.001215558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007615085,"about_ca_topic_score_gemma":0.01022087,"domain_scores_codex":[0.9988319,0.0002484429,0.0001063409,0.0002995656,0.0003593845,0.0001543309],"domain_scores_gemma":[0.9967967,0.001026346,0.0001111322,0.0003459723,0.001544442,0.0001754756],"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":[0.000918789,0.0003123494,0.0131069,0.0001194105,0.0006878151,0.00009894893,0.0001087452,0.1398522,0.0284868,0.001337715,0.00397811,0.8109922],"study_design_scores_gemma":[0.00001420766,0.00008757041,0.006438227,0.00001635259,0.0001716708,0.00005998959,0.00003594108,0.9829145,0.008663012,0.0009947388,0.0005754345,0.00002846511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2237161,0.002560929,0.7659543,0.0003601726,0.0003638907,0.0001347712,0.0004591425,0.002914713,0.003535933],"genre_scores_gemma":[0.8542966,0.0005681156,0.1399341,0.0001160968,0.000144201,0.00009654557,0.0008943337,0.000163667,0.003786271],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007615085,"threshold_uncertainty_score":0.01514155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03782214546971913,"score_gpt":0.2895338379360944,"score_spread":0.2517116924663753,"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."}}