{"id":"W3163002722","doi":"10.1109/icassp39728.2021.9413884","title":"Capturing Banding in Images: Database Construction and Objective Assessment","year":2021,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Artifact (error); Construct (python library); Image quality; Computer vision; Image (mathematics); Grayscale; Class (philosophy); Database; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003189533,0.00008058785,0.0001136521,0.00007903882,0.00007336575,0.0002374816,0.000112239,0.00002236433,0.00002860413],"category_scores_gemma":[0.00002968975,0.00007850075,0.00001833784,0.0002332643,0.00003019428,0.0009525193,0.0003015639,0.0001284266,0.000003224844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000905444,"about_ca_system_score_gemma":0.0001404093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002073977,"about_ca_topic_score_gemma":0.00009052957,"domain_scores_codex":[0.9990567,0.000112733,0.0001662925,0.0003421312,0.0001546727,0.0001674634],"domain_scores_gemma":[0.999509,0.00009420929,0.00003619815,0.0002616731,0.00005170716,0.00004722551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008339989,0.000338726,0.06441307,0.0001952129,0.00007293322,0.001126273,0.004170119,0.00008687595,0.05896983,0.7313015,0.0006537676,0.1386634],"study_design_scores_gemma":[0.005440671,0.0001842903,0.2650145,0.0005904857,0.00004372013,0.001218955,0.02754075,0.1079188,0.553203,0.03474215,0.002345159,0.001757474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03487427,0.0001031919,0.952531,0.001001905,0.0001940788,0.00007788637,0.000002550065,0.00005438149,0.01116068],"genre_scores_gemma":[0.6885722,0.00003897517,0.3109502,0.0002732739,0.000021653,0.000007492768,0.000004483292,0.000002876813,0.0001288158],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6965593,"threshold_uncertainty_score":0.3201168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019972079839014,"score_gpt":0.3134371766992164,"score_spread":0.2932374559008263,"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."}}