{"id":"W3086609496","doi":"10.48550/arxiv.2009.05671","title":"Inverse mapping of face GANs","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Artificial intelligence; Face (sociological concept); Image (mathematics); Generative grammar; Fidelity; Computer vision; Generative model; Pattern recognition (psychology)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001419998,0.0002629387,0.0003952264,0.0001528159,0.00008745489,0.00006201752,0.001659004,0.0001840626,0.00003284945],"category_scores_gemma":[0.00004964185,0.0003055793,0.0002560432,0.0006326483,0.0001102914,0.0003054168,0.002201356,0.0003860895,0.00006236459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007574315,"about_ca_system_score_gemma":0.000169427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001312983,"about_ca_topic_score_gemma":0.0000220983,"domain_scores_codex":[0.9983983,0.0001618185,0.0002089515,0.0008861144,0.00008739602,0.000257432],"domain_scores_gemma":[0.9984586,0.00007985814,0.0002920151,0.0008749429,0.0001357012,0.0001588453],"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":[0.00001571184,0.00005855299,0.0006970612,0.0001129841,0.0001911526,0.0002033971,0.001191969,0.9599041,0.001248972,0.03298372,0.002370074,0.001022252],"study_design_scores_gemma":[0.0002453163,0.00003199832,0.0004195373,0.00007876365,0.00004209496,9.106216e-7,0.0002109499,0.9831185,0.001694259,0.01244117,0.001378731,0.0003378173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01903978,0.00003951522,0.9767056,0.0003757428,0.0004899282,0.0001917759,0.00001511702,0.0001167516,0.003025804],"genre_scores_gemma":[0.9864228,0.0001172539,0.01264726,0.0001603847,0.00009482877,3.491875e-7,0.000006592659,0.00001248683,0.0005380053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.967383,"threshold_uncertainty_score":0.9999396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048473806859068,"score_gpt":0.1800337870786682,"score_spread":0.07518640639276138,"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."}}