{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007007629,0.0005429856,0.00041885,0.001549862,0.0001829682,0.0006701764,0.0003643627,0.0004134568,0.002241771],"category_scores_gemma":[0.003848806,0.0001160764,0.0004356239,0.0006948711,0.0002999939,0.0007369529,0.0007100225,0.0003393747,0.0007530011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004253083,"about_ca_system_score_gemma":0.0001875866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004479296,"about_ca_topic_score_gemma":0.007014047,"domain_scores_codex":[0.9993483,0.00009435759,0.00005013186,0.0001534171,0.0002909923,0.00006265145],"domain_scores_gemma":[0.9981445,0.0003377128,0.0002786665,0.0002414433,0.0008822679,0.0001153851],"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":[0.004472101,0.000761176,0.1692732,0.00395881,0.0008948784,0.001072969,0.001098714,0.03701966,0.1597383,0.001838786,0.0339137,0.5859576],"study_design_scores_gemma":[0.0001333906,0.001763113,0.7005116,0.0003075371,0.0003964593,0.00207907,0.001548763,0.2041778,0.06924031,0.00199337,0.01767357,0.0001749665],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9324674,0.00325232,0.04773584,0.0002328372,0.0001588878,0.000373095,0.007663448,0.0008066719,0.007309623],"genre_scores_gemma":[0.9648727,0.0009233776,0.02456008,0.0001068321,0.00007171254,0.00009399702,0.006902322,0.00009778338,0.00237129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004479296,"threshold_uncertainty_score":0.008906424,"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."}}