{"id":"W3035595647","doi":"10.1109/cvpr42600.2020.00373","title":"Perceptual Quality Assessment of Smartphone Photography","year":2020,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":352,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Photography; Computer science; Image quality; Computer vision; Artificial intelligence; Perception; Quality (philosophy); Computational photography; Camera phone; Ranking (information retrieval); Image (mathematics); Database; Information retrieval; Multimedia; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004578846,0.0001202182,0.0002603342,0.00005083229,0.00005217984,0.0000713445,0.0006939557,0.00003821536,0.0002774073],"category_scores_gemma":[0.00002778467,0.0001041499,0.0001562814,0.0005064255,0.00006141612,0.000380604,0.000296292,0.0001228149,0.00002744047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001603129,"about_ca_system_score_gemma":0.0001161911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001709425,"about_ca_topic_score_gemma":0.000008277346,"domain_scores_codex":[0.9983423,0.0001963285,0.0004254069,0.000351273,0.0004804715,0.0002042389],"domain_scores_gemma":[0.9990661,0.00009990823,0.0001200808,0.000458874,0.0001055237,0.0001495285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002866175,0.00109658,0.0451005,0.0003486353,0.0002193796,0.00002493354,0.01369307,0.00007544289,0.1305363,0.7360267,0.01866091,0.05418885],"study_design_scores_gemma":[0.003523314,0.001814689,0.7565809,0.00004672147,0.00004559924,0.00000817038,0.005442912,0.108737,0.09772763,0.005286739,0.01923933,0.001546913],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05141084,0.00001994196,0.9238555,0.004634998,0.0001062688,0.0001359265,0.000004391829,0.0001570902,0.01967499],"genre_scores_gemma":[0.8609774,0.000006879259,0.1349579,0.003947792,0.00003607774,0.000007292281,0.000002821511,0.000004218331,0.00005968774],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8095665,"threshold_uncertainty_score":0.4247108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09962423024714896,"score_gpt":0.3701245449055414,"score_spread":0.2705003146583925,"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."}}