{"id":"W2102213957","doi":"10.1109/pac.1991.164667","title":"A 256 channel digital filter for a data acquisition system","year":2002,"lang":"en","type":"article","venue":"","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Multiplexer; Computer science; Channel (broadcasting); Filter (signal processing); Multiplexing; Alias; Digital filter; Bandwidth (computing); Analogue filter; Data acquisition; Computer hardware; Microcomputer; Sampling (signal processing); Digital signal processing; Low-pass filter; Electronic engineering; 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":[0.0008634239,0.001115703,0.0008524655,0.001850552,0.0013081,0.001613815,0.001297393,0.001333994,0.1249299],"category_scores_gemma":[0.002152946,0.0004750549,0.0003654611,0.00148174,0.000376297,0.00134142,0.0007236645,0.001385675,0.04709707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001319381,"about_ca_system_score_gemma":0.001581712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001481052,"about_ca_topic_score_gemma":0.00154155,"domain_scores_codex":[0.9984925,0.0000980773,0.0001140937,0.000438831,0.0006940607,0.0001623333],"domain_scores_gemma":[0.9987281,0.0002168808,0.0000520573,0.0002058836,0.0007081092,0.00008900448],"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":[0.001628799,0.0004110598,0.001623712,0.0007573804,0.00007177243,0.0007752694,0.0003747421,0.001430241,0.3972455,0.01686021,0.161419,0.4174024],"study_design_scores_gemma":[0.0002549051,0.0007258168,0.00272798,0.0001297837,0.00008842651,0.001657957,0.00009192298,0.02569414,0.2881637,0.003081277,0.6772181,0.0001658943],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03379712,0.001194984,0.8288968,0.001894939,0.004005067,0.003027359,0.006944285,0.0533672,0.06687223],"genre_scores_gemma":[0.1608405,0.0008251002,0.6722681,0.003003728,0.001166095,0.00358146,0.00824129,0.002449048,0.1476248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1249299,"threshold_uncertainty_score":0.4179323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04151983031447137,"score_gpt":0.2101400650918769,"score_spread":0.1686202347774055,"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."}}