{"id":"W2001167858","doi":"10.1117/12.468022","title":"<title>Cross-switching in asymmetrical coding for stereoscopic video</title>","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Computer vision; Stereoscopy; Artificial intelligence; Image quality; Coding (social sciences); Multiview Video Coding; Video processing; Video tracking; Image (mathematics); 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":[],"consensus_categories":[],"category_scores_codex":[0.00052366,0.0001764113,0.0002527027,0.0001286364,0.00005893635,0.0001994283,0.0008845706,0.0001199269,0.0000396956],"category_scores_gemma":[0.0004021265,0.0001552434,0.0002995246,0.0003438706,0.00005707386,0.0005069272,0.0001755789,0.000204353,0.0000161746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001428221,"about_ca_system_score_gemma":0.00001939936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002281753,"about_ca_topic_score_gemma":8.672581e-8,"domain_scores_codex":[0.9984728,2.611905e-8,0.0004608698,0.000306254,0.0004504969,0.000309614],"domain_scores_gemma":[0.9990406,0.0001645225,0.0001762277,0.00006417961,0.0004837638,0.00007068973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008487534,0.00008753933,0.0001741293,0.0002665554,0.00008342799,1.550254e-7,0.0001660289,0.0000138005,0.04991672,0.9354005,0.01008615,0.003796535],"study_design_scores_gemma":[0.002990804,0.000614816,0.002199307,0.0008688654,0.0001113084,0.0000303493,0.0003082891,0.7961041,0.05489969,0.01370825,0.1270567,0.001107556],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486866,0.000306605,0.009765835,0.003306123,0.0007263555,0.000631749,0.00002129716,0.0001384164,0.03641705],"genre_scores_gemma":[0.6820918,0.0001415443,0.3147461,0.0003761929,0.000651936,0.0001478247,0.000004474354,0.00006045538,0.001779663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9216923,"threshold_uncertainty_score":0.633064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02393242706185511,"score_gpt":0.2749803725378647,"score_spread":0.2510479454760096,"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."}}