{"id":"W1907847775","doi":"10.1007/978-3-319-11758-4_19","title":"Unconstrained Structural Similarity-Based Optimization","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Closeness; Computer science; Measure (data warehouse); Similarity (geometry); Similarity measure; Fidelity; Set (abstract data type); Structural similarity; Euclidean distance; Artificial intelligence; Image processing; Euclidean geometry; Image (mathematics); Image quality; Data mining; Pattern recognition (psychology); Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001032696,0.000547954,0.000544194,0.0006829705,0.0003247836,0.0008886163,0.002921873,0.0003316099,0.00005835506],"category_scores_gemma":[0.0001074215,0.0005062735,0.0001575349,0.0004983277,0.0006936919,0.0005462674,0.0007234446,0.0007408731,0.00002098041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003199567,"about_ca_system_score_gemma":0.001016038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002089943,"about_ca_topic_score_gemma":0.00003894342,"domain_scores_codex":[0.9960977,0.00008301649,0.0005954859,0.001452294,0.00112478,0.0006466762],"domain_scores_gemma":[0.997157,0.0004919612,0.0003469721,0.00148349,0.0003358692,0.0001846951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003700138,0.000009630411,0.0000215647,0.00004489637,0.000007145369,0.00003782205,0.0001708449,0.7076714,0.00002352846,0.03145728,0.00001897692,0.2605332],"study_design_scores_gemma":[0.0003469394,0.0001333356,0.00002424909,0.0001780302,0.000007714672,0.00002141084,7.251977e-8,0.9445741,0.0007397135,0.05288222,0.0005059798,0.0005862861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000009847906,0.0000688058,0.993661,0.00203012,0.00142759,0.0003457468,0.000006057151,0.0002140798,0.002236676],"genre_scores_gemma":[0.09624349,0.000003557243,0.8977613,0.00537342,0.0003940242,0.000006119298,0.00002274299,0.00002891235,0.0001664121],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2599469,"threshold_uncertainty_score":0.9997389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993652703317296,"score_gpt":0.275322763283599,"score_spread":0.2553862362504261,"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."}}