{"id":"W2535540567","doi":"10.1145/2996296","title":"Subjective and Objective Visual Quality Assessment of Textured 3D Meshes","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Applied Perception","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Rendering (computer graphics); Polygon mesh; Quality assessment; Computer graphics; Texture mapping; Visualization; Quality (philosophy); Quality Score; Set (abstract data type)","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":[0.0005313444,0.0001930612,0.000267434,0.0001619645,0.0001955817,0.00005705338,0.0003284727,0.0001104647,0.0001216781],"category_scores_gemma":[0.00001596822,0.0001452755,0.00008674859,0.0002532096,0.0001327681,0.0004604439,0.00002615433,0.0001634469,0.00002333136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002030532,"about_ca_system_score_gemma":0.0000936162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009587129,"about_ca_topic_score_gemma":0.00005065971,"domain_scores_codex":[0.9983003,0.0001975815,0.0003563185,0.0005219164,0.0004034091,0.000220497],"domain_scores_gemma":[0.9986887,0.0003750877,0.000143549,0.0006021555,0.0001114484,0.00007905759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00008206225,0.0005214673,0.0003608861,0.00003524172,0.00008359576,7.096017e-7,0.002951529,0.00004052847,0.2444153,0.00984207,0.00001442642,0.7416521],"study_design_scores_gemma":[0.00299315,0.0009235739,0.9204432,0.00009862107,0.00008231747,0.00001134226,0.003523695,0.002374366,0.05181595,0.01673501,0.0002286379,0.000770138],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1300471,0.000004110027,0.8673499,0.0006751599,0.0001020302,0.0003071125,0.00001611777,0.0001032813,0.001395188],"genre_scores_gemma":[0.9452708,0.00005357778,0.0542452,0.0001833032,0.00002729079,0.00009433783,0.000002579861,0.00001041669,0.0001124246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9200823,"threshold_uncertainty_score":0.5924163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0319504471451502,"score_gpt":0.3509928161147665,"score_spread":0.3190423689696162,"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."}}