{"id":"W2150532551","doi":"10.1109/icassp.1985.1168127","title":"A two-dimensional digital filter chip set for modular two-dimensional filter implementation","year":2005,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Modular design; Computer science; Digital filter; Chip; Computer hardware; Half-band filter; Filter (signal processing); Set (abstract data type); Chipset; NMOS logic; Electronic engineering; Engineering; Computer vision; Root-raised-cosine filter; Electrical engineering; Telecommunications","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":[0.0003218385,0.0004553793,0.0004254269,0.0005517579,0.000361046,0.0004606885,0.0008194642,0.0003582702,0.004673879],"category_scores_gemma":[0.0006864105,0.0002741066,0.000383627,0.0003044864,0.0002490273,0.0004622142,0.0003892612,0.0004796283,0.001341785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005310162,"about_ca_system_score_gemma":0.0007587995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003676528,"about_ca_topic_score_gemma":0.0007455823,"domain_scores_codex":[0.9997255,0.00002574151,0.00001646866,0.00004019044,0.0001421974,0.00004994088],"domain_scores_gemma":[0.9994859,0.00008932866,0.00004734785,0.0000987344,0.0002228707,0.00005586772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002239521,0.0001450563,0.0009185951,0.0002317415,0.00004778977,0.0002281064,0.00008718771,0.005415531,0.9039369,0.01273549,0.003272066,0.07275766],"study_design_scores_gemma":[0.0001094149,0.001249027,0.003217056,0.0000269503,0.00006801577,0.0008464215,0.0000246163,0.03470207,0.926428,0.001353704,0.03190336,0.00007130058],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2659579,0.0002989842,0.7163202,0.0002415091,0.0002218105,0.0005142343,0.0006246339,0.003858707,0.01196201],"genre_scores_gemma":[0.5594894,0.0001229055,0.4328312,0.0001757333,0.00004024113,0.0005005024,0.0006966417,0.0001198774,0.006023487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004673879,"threshold_uncertainty_score":0.01563567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455762572608437,"score_gpt":0.2667336267369297,"score_spread":0.2521760010108454,"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."}}