{"id":"W2131396638","doi":"10.1109/mwscas.2000.951672","title":"A VLSI architecture for soft-output PR4 detection","year":2002,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Application-specific integrated circuit; Very-large-scale integration; Kernel (algebra); Computer science; CMOS; Electronic engineering; Limiter; Chip; Metric (unit); Soft error; Architecture; Embedded system; Parallel computing; Engineering; Mathematics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001068521,0.0003049806,0.0001545093,0.000305103,0.000257415,0.0005359151,0.001210534,0.0003548317,0.003745472],"category_scores_gemma":[0.0002167413,0.0001551194,0.0001869008,0.0002173939,0.0002056495,0.0004442256,0.0002144595,0.0003199074,0.001736328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000510168,"about_ca_system_score_gemma":0.0004551883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007528763,"about_ca_topic_score_gemma":0.001574386,"domain_scores_codex":[0.9998831,0.00001320437,0.000006262942,0.00002701225,0.0000480204,0.00002241103],"domain_scores_gemma":[0.9998714,0.00001866966,0.00001884403,0.00002053159,0.00005930903,0.00001125427],"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":[0.0002109574,0.0001031342,0.001338494,0.0002485752,0.00006087311,0.0002670269,0.0001086024,0.008280978,0.7892765,0.02113645,0.006662258,0.1723061],"study_design_scores_gemma":[0.000117847,0.001964173,0.003587295,0.0000504203,0.0001761583,0.00207807,0.00006513736,0.1832612,0.7117554,0.009543022,0.08731888,0.00008247125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1655489,0.000926481,0.8026913,0.0004608865,0.0002328081,0.0002221505,0.0004049764,0.008400479,0.02111186],"genre_scores_gemma":[0.7183362,0.0002964172,0.2676147,0.00029757,0.00006813598,0.0001135152,0.0003513006,0.00009608714,0.01282611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003745472,"threshold_uncertainty_score":0.01252985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01787366368346947,"score_gpt":0.1829452556758489,"score_spread":0.1650715919923795,"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."}}