{"id":"W4400234622","doi":"10.1109/iscas58744.2024.10557966","title":"SAR-MemPipe: A Hybrid Pipeline-SAR Memristive ADC for Analog Resistive Arrays","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Successive approximation ADC; Pipeline (software); Resistive touchscreen; Computer science; Synthetic aperture radar; Electronic engineering; Artificial intelligence; Electrical engineering; Capacitor; Engineering; Computer vision; Voltage","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":[0.0001292842,0.0002192943,0.0002208389,0.0001004277,0.0001024163,0.00004472935,0.0001226925,0.00004504603,0.00006519986],"category_scores_gemma":[0.00009339154,0.0001969905,0.0001298316,0.0002115567,0.0000299762,0.0001655181,0.00003247984,0.0002263209,0.00007963179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007222474,"about_ca_system_score_gemma":0.00001938977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003084773,"about_ca_topic_score_gemma":0.000005491273,"domain_scores_codex":[0.9989656,0.0000130801,0.0002450111,0.0003313745,0.0001026285,0.0003423485],"domain_scores_gemma":[0.9992984,0.0003778057,0.00001674077,0.0001668056,0.00005193495,0.00008831066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003542691,0.00009260193,0.00005048007,0.002547274,0.0006047142,0.0008638357,0.001792574,0.3371699,0.137065,0.02059538,0.2570228,0.2418412],"study_design_scores_gemma":[0.0003849021,0.0001051987,0.00002721978,0.0002127097,0.0000686179,0.00003896135,0.0002655639,0.523451,0.3451287,0.005417819,0.1243364,0.0005628545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03026855,0.001541706,0.9506125,0.0001714873,0.001104359,0.0003955538,0.00009988808,0.001609581,0.01419634],"genre_scores_gemma":[0.9845678,0.00005280747,0.01180386,0.0001504726,0.0006107206,0.00001437754,0.00003669034,0.00006520256,0.002698016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9542993,"threshold_uncertainty_score":0.8033041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927429833523163,"score_gpt":0.2666665630822616,"score_spread":0.24739226474703,"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."}}