{"id":"W4409573349","doi":"10.61091/jcmcc127a-041","title":"Dataset-driven new set of video quality evaluations towards reference-free video quality evaluations","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Video quality; Quality (philosophy); Set (abstract data type); Subjective video quality; Video recording; Artificial intelligence; Multimedia; Image quality; Image (mathematics); Engineering; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004484034,0.001979703,0.00119912,0.004435549,0.0007204872,0.002380308,0.002328219,0.001728591,0.00288957],"category_scores_gemma":[0.0151442,0.0002469961,0.001349145,0.002946932,0.0008026448,0.002508996,0.002245365,0.001865953,0.001814874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002356038,"about_ca_system_score_gemma":0.00117676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000739,"about_ca_topic_score_gemma":0.01441467,"domain_scores_codex":[0.9932489,0.001117121,0.0008366885,0.001391254,0.003054152,0.0003519558],"domain_scores_gemma":[0.9917958,0.001028453,0.0008333072,0.00149603,0.004420599,0.0004258764],"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":[0.003181855,0.002448486,0.04951107,0.005206349,0.00135211,0.0008671111,0.0003110631,0.06590185,0.025194,0.008322924,0.3621164,0.4755868],"study_design_scores_gemma":[0.0009536361,0.002554197,0.1814048,0.001872049,0.0009860396,0.002738888,0.001230481,0.4701332,0.05160811,0.01435211,0.2716188,0.000547623],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2715943,0.009861472,0.21697,0.002209165,0.002986122,0.004630991,0.4338327,0.01381425,0.04410095],"genre_scores_gemma":[0.2854517,0.00148791,0.09470844,0.000665359,0.0003879332,0.001793956,0.6095959,0.0005612497,0.005347617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01000739,"threshold_uncertainty_score":0.02371407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048400985245941,"score_gpt":0.4299483792770031,"score_spread":0.3251082807524091,"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."}}