{"id":"W4285192846","doi":"10.1007/978-3-031-06427-2_23","title":"Landmark-Guided Conditional GANs for Face Aging","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Memorial University of Newfoundland","funders":"","keywords":"Discriminative model; Computer science; Landmark; Consistency (knowledge bases); Artificial intelligence; Task (project management); Identity (music); Face (sociological concept); Generative grammar; Computer vision; Scope (computer science); Aesthetics; Art","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":[0.0008713783,0.0004260974,0.0004476625,0.0004520072,0.0006128498,0.0004619824,0.002446072,0.0001418881,0.0001561701],"category_scores_gemma":[0.000101474,0.0004090967,0.0001951075,0.0003756041,0.0003556148,0.0006205898,0.001110772,0.0005014443,0.00001427543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002832823,"about_ca_system_score_gemma":0.0004686333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001557207,"about_ca_topic_score_gemma":0.00003125462,"domain_scores_codex":[0.9968031,0.00004756798,0.0004141603,0.001354695,0.0007733026,0.0006071429],"domain_scores_gemma":[0.9977979,0.0007944443,0.0002415714,0.0008247623,0.0002094553,0.0001318789],"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":[0.00000797503,0.00003408953,0.00003238343,0.00003688106,0.00003846966,0.00005912173,0.0007629509,0.6907572,0.0002396486,0.06533719,0.001491957,0.2412021],"study_design_scores_gemma":[0.0003703019,0.0001273756,0.00004582043,0.00007823204,0.00001146053,0.00004721712,3.215052e-7,0.8275111,0.001131208,0.1320753,0.03796784,0.000633848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000006916243,0.0002668669,0.9920542,0.001965532,0.001957284,0.0005017729,0.00004632826,0.0001011381,0.003099992],"genre_scores_gemma":[0.1426778,0.00006083311,0.8492686,0.004266957,0.001677761,0.00008501077,0.00009097008,0.0000657573,0.001806274],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2405683,"threshold_uncertainty_score":0.9998361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02405885272442756,"score_gpt":0.2567023633890416,"score_spread":0.232643510664614,"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."}}