{"id":"W4391926338","doi":"10.1007/s11227-024-05912-5","title":"Meta generative image and text data augmentation optimization","year":2024,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Discriminator; Computer science; Generator (circuit theory); Generative grammar; Artificial intelligence; Machine learning; Intuition; Domain (mathematical analysis); Generative model; Image (mathematics); Data mining; Pattern recognition (psychology); Mathematics","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":[0.001078107,0.001304762,0.001239892,0.0009417878,0.000402761,0.001180422,0.002092072,0.002506464,0.007712832],"category_scores_gemma":[0.00403471,0.0007752141,0.001551937,0.001050992,0.001135899,0.001498004,0.002205141,0.002478529,0.002805779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007730669,"about_ca_system_score_gemma":0.0009359127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002842425,"about_ca_topic_score_gemma":0.004590174,"domain_scores_codex":[0.9994436,0.0001497602,0.00002226133,0.000187568,0.0001314195,0.00006536899],"domain_scores_gemma":[0.9985099,0.0008872494,0.00007951094,0.0003026125,0.0001598581,0.0000607807],"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":[0.0002512613,0.0001428612,0.0004081264,0.0001317686,0.00009644499,0.0001538316,0.00006355528,0.7839429,0.00959501,0.0187536,0.009373073,0.1770876],"study_design_scores_gemma":[0.00000722417,0.00001170467,0.00002881443,0.000003116651,0.000007009442,0.00001830107,0.000003700705,0.9926906,0.001782725,0.004876025,0.0005669002,0.000003910815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01014506,0.0003084024,0.9829301,0.000590863,0.0001728458,0.00007067595,0.000388203,0.00250586,0.002887979],"genre_scores_gemma":[0.4779857,0.0004298575,0.4880654,0.001085639,0.0005105185,0.0004640976,0.002119886,0.001356647,0.02798222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007712832,"threshold_uncertainty_score":0.02580202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06707860647216189,"score_gpt":0.2854487057895803,"score_spread":0.2183700993174184,"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."}}