{"id":"W4394629225","doi":"10.1109/csce60160.2023.00362","title":"Meta Generative Data Augmentation Optimization","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Hokkaido University","keywords":"Computer science; Generative grammar; Artificial intelligence","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":[0.0001921975,0.00005518706,0.00007843338,0.00004973378,0.00008545376,0.00004509413,0.0003351418,0.00001149385,0.00006165082],"category_scores_gemma":[0.0000179214,0.00004099427,0.00001407326,0.000396637,0.000009918639,0.001745183,0.0004559244,0.00001912932,0.0001152722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007281146,"about_ca_system_score_gemma":0.00001875697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003213286,"about_ca_topic_score_gemma":0.00001587971,"domain_scores_codex":[0.9993759,0.00003396759,0.000108196,0.0002630381,0.0001274077,0.00009151349],"domain_scores_gemma":[0.9991672,0.00003141946,0.00003687455,0.0007066327,0.00003246953,0.00002538921],"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":[0.000001825347,0.00001460199,0.00001889241,0.00001059791,0.0002525704,0.00001095933,0.0004691318,0.2496826,0.0006111371,0.7052087,0.03482534,0.008893676],"study_design_scores_gemma":[0.00007385853,0.000008398571,0.00002143342,0.000001282506,0.00001948009,0.000001661047,0.0000590429,0.9798655,0.001076582,0.0002495386,0.01855441,0.00006882785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003026152,0.00004440538,0.9975531,0.0006866656,0.0001869217,0.00008578949,0.00004189536,0.000311874,0.001059134],"genre_scores_gemma":[0.001046354,0.00004797127,0.9951901,0.0002265161,0.00004810113,0.00002150626,0.0007719536,0.000004450995,0.002642975],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7301829,"threshold_uncertainty_score":0.1671698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1968259845324093,"score_gpt":0.3398827807319934,"score_spread":0.1430567961995841,"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."}}