{"id":"W7009019700","doi":"","title":"A deep generative model framework for creating
\\nhigh quality synthetic transaction sequences","year":2023,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Financial Distress and Bankruptcy Prediction","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Mitacs","keywords":"Synthetic data; Database transaction; Transaction data; Generative model; Quality (philosophy); Credit card; Generative grammar; Data modeling","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001166783,0.0005837174,0.0008087938,0.001802491,0.00363959,0.00062633,0.001230812,0.001171801,0.00006052301],"category_scores_gemma":[0.0007442466,0.0007087789,0.0006303877,0.002251392,0.0003352269,0.001823905,0.0001918747,0.001294559,0.00008156546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101345,"about_ca_system_score_gemma":0.0008121592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01289666,"about_ca_topic_score_gemma":0.00728153,"domain_scores_codex":[0.9953935,0.0003289778,0.0004968747,0.001392263,0.001452754,0.0009356303],"domain_scores_gemma":[0.9961261,0.000614651,0.0006549621,0.0005951063,0.00190186,0.0001073587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.05743959,0.001584532,0.0005957541,0.006732317,0.001780761,0.001968618,0.006644445,0.02881192,0.02153724,0.8470971,0.01559819,0.01020951],"study_design_scores_gemma":[0.02749832,0.002112156,0.009462388,0.006709626,0.00816583,0.00001803511,0.181055,0.3449325,0.01745169,0.1660404,0.2246078,0.01194626],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7468662,0.00009593356,0.04917225,0.0004143514,0.04973085,0.005117664,0.0004110313,0.001688111,0.1465036],"genre_scores_gemma":[0.8323594,0.0002876231,0.00147817,0.00003488441,0.03411815,0.00002181429,0.002743979,0.0002463698,0.1287096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6810567,"threshold_uncertainty_score":0.9995363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04809184682306289,"score_gpt":0.2923482533369813,"score_spread":0.2442564065139184,"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."}}