{"id":"W6966492707","doi":"10.48550/arxiv.1912.07126","title":"Characterizing Generalized Rate-Distortion Performance of Video Coding: An Eigen Analysis Approach","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Codec; Set (abstract data type); Encoding (memory); Lossy compression; Subspace topology; Function (biology); Data compression; Regular polygon","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":[0.002210801,0.001143938,0.0007982779,0.001363709,0.0002025589,0.001062415,0.0009504306,0.0008358327,0.0008522036],"category_scores_gemma":[0.009765849,0.0003304323,0.0005843338,0.0008693414,0.001247409,0.001718203,0.001150355,0.00123583,0.0003157495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001009563,"about_ca_system_score_gemma":0.0006146831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002183129,"about_ca_topic_score_gemma":0.001104359,"domain_scores_codex":[0.9988648,0.0004974259,0.00005450927,0.0001612414,0.0003546944,0.00006733924],"domain_scores_gemma":[0.9961999,0.002328928,0.0003360449,0.0005708728,0.00047195,0.00009229531],"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":[0.0001244905,0.00009564582,0.002799754,0.0001526177,0.0001109752,0.0001018694,0.0001250532,0.7915115,0.01887817,0.08412161,0.001865856,0.1001124],"study_design_scores_gemma":[0.000001605644,0.00001984609,0.0003579361,0.000005144747,0.000003380108,0.00003324695,0.00000685352,0.9893001,0.001408181,0.008630046,0.000224453,0.000009266102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01731422,0.0003542183,0.9812261,0.0001764924,0.00001363154,0.00002184651,0.00007725461,0.0001397941,0.0006765111],"genre_scores_gemma":[0.7116409,0.001682505,0.2829315,0.0002323995,0.0001573278,0.0001820032,0.0005678745,0.0002503282,0.002355078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002210801,"threshold_uncertainty_score":0.01169193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103511164962551,"score_gpt":0.2271714175522906,"score_spread":0.1236602525897396,"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."}}