{"id":"W4376129969","doi":"10.20944/preprints202305.0777.v1","title":"Data Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Model","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Overfitting; Computer science; Categorical variable; Machine learning; Artificial intelligence; Generative grammar; Artificial neural network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001913168,0.0006908416,0.0004836111,0.0008084698,0.0003042644,0.0005647172,0.0009243283,0.0008475335,0.002557188],"category_scores_gemma":[0.005441385,0.0002945643,0.001046623,0.000574414,0.0005550798,0.0008633763,0.001176197,0.001624285,0.0007598787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000661143,"about_ca_system_score_gemma":0.0008296264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00420052,"about_ca_topic_score_gemma":0.004076111,"domain_scores_codex":[0.9993472,0.0002308809,0.00004470976,0.0001913637,0.0001309588,0.00005500727],"domain_scores_gemma":[0.9980543,0.001036406,0.0001371747,0.0003337852,0.0003877955,0.00005062882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004568724,0.0001443326,0.007258874,0.0002687438,0.0001332235,0.0003282433,0.0001958124,0.6617578,0.02261398,0.01472481,0.005044918,0.2870724],"study_design_scores_gemma":[0.000009934461,0.00005826319,0.0009516518,0.00001425067,0.00001573938,0.00006475494,0.00002444424,0.9862292,0.006034363,0.004904174,0.001678971,0.00001429559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04162553,0.0004293872,0.9532384,0.0005100621,0.0001333431,0.0001518316,0.001184001,0.001188893,0.001538496],"genre_scores_gemma":[0.6162356,0.0004738428,0.371157,0.0003339474,0.00009459569,0.0005431052,0.006102523,0.000185346,0.004874066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00420052,"threshold_uncertainty_score":0.01011795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5677361068086789,"score_gpt":0.4366417347552346,"score_spread":0.1310943720534443,"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."}}