{"id":"W1579790087","doi":"10.1109/acssc.1995.540850","title":"Real-time 3-dimensional recursive digital filter for video signals","year":2002,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"NTSC; Computer science; Filter (signal processing); Adaptive filter; Interconnectivity; Digital filter; Filter design; Computer hardware; Real-time computing; Path (computing); Pixel; Computer vision; Algorithm; Artificial intelligence; High-definition television","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008048106,0.0001219823,0.000115818,0.00007358933,0.00007000892,0.0004971199,0.0003486236,0.00002424667,0.0007671053],"category_scores_gemma":[0.00003792715,0.0001050702,0.00007790466,0.0001669432,0.00002073548,0.002010701,0.0001003246,0.00002673336,0.0009560374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002636544,"about_ca_system_score_gemma":0.00001515688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003463919,"about_ca_topic_score_gemma":2.869223e-7,"domain_scores_codex":[0.9989495,0.00001363925,0.0002215925,0.0003212423,0.0002244168,0.0002696115],"domain_scores_gemma":[0.9992644,0.0002130401,0.00006115342,0.000252577,0.0001093925,0.00009942504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001601246,0.0001661758,0.00002947007,0.000008895026,0.00004063829,0.00001050402,0.0003284687,0.00002636132,0.01291619,0.04570873,0.863086,0.07766259],"study_design_scores_gemma":[0.005031994,0.003314306,0.0005395047,0.0001096722,0.00003635685,0.0001738141,0.00008886766,0.45399,0.1099795,0.1874768,0.2370335,0.002225849],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0113589,0.00002541495,0.7756924,0.002899604,0.0004161079,0.001009222,0.0001605536,0.000543415,0.2078944],"genre_scores_gemma":[0.5366865,0.000009219078,0.323531,0.007386928,0.0003971014,0.0002274263,0.000252319,0.00006795285,0.1314416],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6260525,"threshold_uncertainty_score":0.9998218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03722554878825048,"score_gpt":0.2600261940431312,"score_spread":0.2228006452548807,"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."}}