{"id":"W3014415704","doi":"10.1109/cvpr42600.2020.00147","title":"Deep White-Balance Editing","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Color balance; Computer science; Rendering (computer graphics); Artificial intelligence; RGB color model; Computer vision; Color space; Color image; Computer graphics (images); Image (mathematics); Image processing","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":[0.0004440323,0.001001263,0.0005384512,0.0005124523,0.000372079,0.001278214,0.002031916,0.0007691515,0.01090653],"category_scores_gemma":[0.001624996,0.0003861499,0.0006934687,0.0003096874,0.0005753679,0.001520348,0.001882692,0.001584579,0.001921249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007422691,"about_ca_system_score_gemma":0.0005362013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003423436,"about_ca_topic_score_gemma":0.005485855,"domain_scores_codex":[0.9996042,0.00003444991,0.00001539165,0.0001306894,0.0001584543,0.00005689323],"domain_scores_gemma":[0.9996293,0.00008017214,0.00003195439,0.0001303321,0.00009463377,0.00003370411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002265384,0.000171035,0.0008760035,0.0002005151,0.00007294493,0.0003551069,0.0002702275,0.2055454,0.09218884,0.02309189,0.01710204,0.6598995],"study_design_scores_gemma":[0.00001729797,0.0000625323,0.0002619048,0.00002335093,0.00001678157,0.0001327271,0.00003516631,0.9075339,0.05354941,0.01377343,0.02457116,0.00002228142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01066012,0.0001330883,0.9717041,0.0001463494,0.0001462007,0.00007140761,0.0002318736,0.00964486,0.007261968],"genre_scores_gemma":[0.3598572,0.0003008571,0.6128438,0.0005892033,0.0001064579,0.000162376,0.0009860497,0.002229948,0.02292418],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01090653,"threshold_uncertainty_score":0.03648591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754135776600798,"score_gpt":0.2705147933311318,"score_spread":0.2529734355651238,"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."}}