{"id":"W2375491617","doi":"","title":"Design and Implementation of a Distributed Platform for Handwritten Chinese Character Recognition","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scheduling (production processes); Character recognition; Character (mathematics); Architecture; Middleware (distributed applications); Distributed computing; Artificial intelligence","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":[0.0002157422,0.0001389787,0.0001782902,0.00008643728,0.0001488933,0.0001294759,0.0003089735,0.00005200609,0.000002028714],"category_scores_gemma":[3.818973e-7,0.0001302418,0.00005569753,0.0002912251,0.00002428319,0.0002289301,0.00008601812,0.00004491739,0.000007594928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002406011,"about_ca_system_score_gemma":0.00003185798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005561541,"about_ca_topic_score_gemma":0.000005594403,"domain_scores_codex":[0.9989884,0.00002437261,0.0003777846,0.0003231845,0.00008931769,0.0001969693],"domain_scores_gemma":[0.9992371,0.0001395423,0.0002034386,0.0002176567,0.0001612693,0.00004098736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004238772,0.0005601474,0.0052517,0.0004232758,0.0001474211,0.000001598852,0.001262681,0.001530527,0.04877513,0.02303557,0.01268245,0.9062871],"study_design_scores_gemma":[0.009720535,0.000673497,0.1634327,0.0001980209,0.0001425783,0.000249388,0.0001192428,0.3179342,0.04153391,0.1203304,0.3435434,0.002122069],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02939192,0.00005908367,0.968621,0.0002224492,0.00002292543,0.001376725,0.000173339,0.0001127693,0.00001979197],"genre_scores_gemma":[0.5248665,0.000003186194,0.4733069,0.00005698231,0.000157196,0.0005861885,0.001000223,0.000009256571,0.00001353102],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.904165,"threshold_uncertainty_score":0.5311106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451758822925278,"score_gpt":0.2625324529485283,"score_spread":0.2480148647192755,"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."}}