{"id":"W4387460482","doi":"10.1145/3626524","title":"Handwritten Odia Digit Recognition using Learning Systems: A Comparison of Neural Networks and Support Vector Machine Models","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Asian and Low-Resource Language Information Processing","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; Python (programming language); Artificial intelligence; Scripting language; Support vector machine; Convolutional neural network; Deep learning; Artificial neural network; Machine learning; Classifier (UML); Natural language processing; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00151882,0.0008584535,0.0008744664,0.001474732,0.0002385201,0.001476597,0.0009098107,0.0008748198,0.0014454],"category_scores_gemma":[0.003465972,0.0002407039,0.0005315061,0.001240371,0.0002451207,0.001929315,0.0005015793,0.0007453567,0.0005230857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009596884,"about_ca_system_score_gemma":0.0005847666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009277633,"about_ca_topic_score_gemma":0.006115963,"domain_scores_codex":[0.9989957,0.0001772596,0.00009265263,0.0001858341,0.0004699553,0.00007860087],"domain_scores_gemma":[0.9982761,0.0008665867,0.0001507228,0.00008886829,0.000570863,0.00004677647],"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":[0.0008156443,0.0003753186,0.01056888,0.0006822273,0.0003476697,0.0001389881,0.00009615796,0.1897396,0.004746904,0.002137894,0.004644032,0.7857067],"study_design_scores_gemma":[0.00001433179,0.0002828555,0.003538018,0.00007275119,0.00005616133,0.0000628272,0.00006886242,0.9879651,0.004757318,0.001040359,0.00211228,0.000029165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5258593,0.04137241,0.3993357,0.001821525,0.001416863,0.0003196387,0.001170266,0.005451874,0.02325252],"genre_scores_gemma":[0.904706,0.006121155,0.08184884,0.0002003586,0.0001893956,0.0001080899,0.001140288,0.00009096787,0.005594925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009277633,"threshold_uncertainty_score":0.01844728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179014338040878,"score_gpt":0.2370358633741443,"score_spread":0.2152457199937355,"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."}}