{"id":"W2129455469","doi":"10.1109/icsmc.1991.169684","title":"Computer algorithms for recognizing the distinct parts of handprinted characters","year":2002,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Pattern recognition (psychology); Decomposition; Scheme (mathematics); Artificial intelligence; Hierarchy; Algorithm; Mathematics; Biology","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":[0.0003373464,0.0001179693,0.0001681796,0.00007113053,0.0001121099,0.0001004294,0.0006335889,0.000045482,0.0001022561],"category_scores_gemma":[0.00003950189,0.00007836468,0.0001132415,0.0002039863,0.00006419342,0.0002569511,0.000154558,0.00008302508,0.00003907494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001500791,"about_ca_system_score_gemma":0.000007141835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001081087,"about_ca_topic_score_gemma":0.00000436957,"domain_scores_codex":[0.9990071,0.00005155932,0.0002901655,0.0002729632,0.0001569217,0.0002213138],"domain_scores_gemma":[0.9989542,0.00029957,0.000127296,0.0003923453,0.0001741065,0.00005242589],"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":[0.000002204572,0.00006903898,0.0001074173,0.00001676236,0.00002187032,0.000001600125,0.0003654724,5.012411e-7,0.0002893161,0.002839467,0.006105569,0.9901808],"study_design_scores_gemma":[0.001059892,0.0005002829,0.004146485,0.0001748783,0.00002749748,0.00006378217,0.00004234241,0.7965124,0.154003,0.007469767,0.03540297,0.0005967539],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002988834,0.0000238993,0.9925534,0.001725796,0.0002319369,0.0004154348,0.000005506445,0.0003304275,0.001724752],"genre_scores_gemma":[0.6587679,0.00002377074,0.3392475,0.0009556772,0.0001497681,0.0001306119,0.000006157957,0.00001449611,0.0007041359],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.989584,"threshold_uncertainty_score":0.3195619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05516415497909053,"score_gpt":0.2652172191097001,"score_spread":0.2100530641306096,"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."}}