{"id":"W4399817052","doi":"10.1002/cjce.25370","title":"Gnireteet","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002150988,0.00005955896,0.00007773657,0.00007056315,0.00003229655,0.0002375851,0.0004619625,0.0000259246,0.00001557166],"category_scores_gemma":[0.00007904539,0.00003898522,0.00007025957,0.0001962351,0.00002124943,0.0001921146,0.00001572026,0.0002011325,0.000007979253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006947842,"about_ca_system_score_gemma":0.0002606926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001519796,"about_ca_topic_score_gemma":0.00002650347,"domain_scores_codex":[0.9995589,0.000008454382,0.0001237583,0.00005840621,0.00009030915,0.0001601998],"domain_scores_gemma":[0.9995592,0.0000794162,0.0000170198,0.0001077601,0.00003965608,0.0001969955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004919341,0.000009405983,0.00003475624,0.0000970859,0.0004615634,0.00146322,0.003357247,0.2987593,0.3312977,0.178716,0.04889291,0.1369059],"study_design_scores_gemma":[0.00006333202,0.00001858041,0.00002041487,0.0001299927,0.00001622943,0.0003254278,0.000002906204,0.8414683,0.1083214,0.001430436,0.04806218,0.0001408858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02094646,0.005589381,0.9578276,0.01159684,0.002791392,0.00005752339,0.000002171904,0.00005391759,0.001134657],"genre_scores_gemma":[0.9940683,0.000001675845,0.005403393,0.00008747275,0.000406108,3.847376e-7,8.33404e-8,0.000005914213,0.00002664869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9731219,"threshold_uncertainty_score":0.2291038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007423251099674105,"score_gpt":0.1798701406801811,"score_spread":0.172446889580507,"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."}}