{"id":"W2750764646","doi":"10.1109/icmew.2017.8026266","title":"Quality assessment of stereoscopic 3D images based on local and global visual characteristics","year":2017,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Stereoscopy; Computer science; Computer vision; Quality (philosophy); Artificial intelligence; Computer graphics (images); Image quality; Image (mathematics)","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":[0.0009365322,0.0005341567,0.0005458895,0.002203963,0.0001901992,0.0009707004,0.0003921319,0.0004094498,0.001342247],"category_scores_gemma":[0.002654324,0.0001691399,0.0005558184,0.0009100743,0.0003841727,0.0009783985,0.0007154697,0.000330921,0.0003611587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003238413,"about_ca_system_score_gemma":0.0002721692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009018325,"about_ca_topic_score_gemma":0.001339947,"domain_scores_codex":[0.9991624,0.0001184949,0.00005715392,0.0001011903,0.0005156143,0.00004509207],"domain_scores_gemma":[0.9985406,0.0001884435,0.0002485181,0.0001823257,0.0007685274,0.00007152095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009350123,0.0001027223,0.01177569,0.000644814,0.0002037863,0.000312514,0.0002397561,0.02403759,0.3716103,0.00289319,0.001793783,0.5854508],"study_design_scores_gemma":[0.00008459033,0.0009866593,0.06420472,0.0001276319,0.0004156848,0.002675078,0.0004332956,0.602402,0.3162678,0.005442346,0.006782158,0.0001780319],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1566914,0.001203213,0.8386698,0.0001343957,0.00007874087,0.0001048554,0.0002515898,0.0006270946,0.002238978],"genre_scores_gemma":[0.7688196,0.001269932,0.2276415,0.00008370564,0.00008704076,0.00005489833,0.0004492371,0.0001023827,0.001491623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002203963,"threshold_uncertainty_score":0.004952967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04589719380693039,"score_gpt":0.4162571891999788,"score_spread":0.3703599953930484,"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."}}