{"id":"W2993921587","doi":"10.1109/cvpr42600.2020.00586","title":"Exploring Unlabeled Faces for Novel Attribute Discovery","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Artificial intelligence; Normalization (sociology); Translation (biology); Bottleneck; Labeled data; Image (mathematics); Pattern recognition (psychology); Image translation; Limiting; Machine learning","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":[0.0002169785,0.0003575796,0.0004924358,0.00006852382,0.0001562884,0.0009486916,0.001444818,0.000112195,0.00000730137],"category_scores_gemma":[0.0001422478,0.000306175,0.0002924922,0.000191763,0.00003092243,0.001313281,0.002459456,0.0002856766,0.00001820061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000055269,"about_ca_system_score_gemma":0.0001541721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006877789,"about_ca_topic_score_gemma":0.00001458735,"domain_scores_codex":[0.9979594,0.00004109623,0.0003456367,0.001013467,0.0002468433,0.000393508],"domain_scores_gemma":[0.9986143,0.0002338346,0.0001756546,0.000710515,0.0001402818,0.0001254589],"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":[0.000169486,0.0007650277,0.0003679297,0.001337319,0.002432979,0.00004422108,0.004829171,0.4455801,0.08750424,0.2700915,0.06079322,0.1260848],"study_design_scores_gemma":[0.0008945879,0.0001482842,0.000522928,0.0001726898,0.00008155831,0.000001839619,0.0001230903,0.8914495,0.07378371,0.006722993,0.02482521,0.00127358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001176095,0.0001311895,0.9888109,0.006256172,0.002301243,0.0006249237,0.00009283648,0.0002414755,0.000365162],"genre_scores_gemma":[0.5189787,0.0001656216,0.4777191,0.0006534913,0.001025031,0.0004635505,0.00005742409,0.00003347444,0.0009037085],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5178025,"threshold_uncertainty_score":0.999939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3021136911512163,"score_gpt":0.288838380592467,"score_spread":0.01327531055874925,"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."}}