{"id":"W2121662690","doi":"10.1109/ccece.2005.1557355","title":"Existing and emerging image quality metrics","year":2006,"lang":"en","type":"article","venue":"","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"SaskTel (Canada); University of Regina","funders":"","keywords":"Consistency (knowledge bases); Computer science; Metric (unit); Image quality; Quality (philosophy); Set (abstract data type); Point (geometry); Monotonic function; Artificial intelligence; Image (mathematics); Data mining; Machine learning; 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":[0.01448017,0.001742338,0.00179252,0.01071548,0.0008472306,0.004328104,0.003302232,0.001416657,0.002347138],"category_scores_gemma":[0.04971259,0.0005242827,0.0009078541,0.00756695,0.002034668,0.006994857,0.00240857,0.001936817,0.0009215508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001896689,"about_ca_system_score_gemma":0.001176857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001926988,"about_ca_topic_score_gemma":0.001731365,"domain_scores_codex":[0.9843606,0.002798835,0.001614135,0.002022059,0.008868885,0.000335487],"domain_scores_gemma":[0.9493212,0.01889272,0.005517307,0.003971219,0.02124903,0.001048617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004308547,0.0002089534,0.01820525,0.002805775,0.0002310155,0.00006931132,0.0004199987,0.007212689,0.0105985,0.02431346,0.005804871,0.9296993],"study_design_scores_gemma":[0.0002084002,0.005088233,0.1179194,0.005602503,0.001515961,0.005164744,0.003583534,0.3466136,0.1092421,0.1558634,0.2479256,0.001272409],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.06589421,0.1813387,0.720765,0.002827597,0.001012189,0.000611772,0.001413312,0.002765285,0.02337186],"genre_scores_gemma":[0.3704565,0.0530964,0.5655464,0.0007018273,0.001568445,0.0005792906,0.002856181,0.0005823054,0.004612694],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01448017,"threshold_uncertainty_score":0.07657939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06485142236597809,"score_gpt":0.3793086315386538,"score_spread":0.3144572091726757,"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."}}