{"id":"W4412718926","doi":"10.1109/tcsii.2025.3592482","title":"An Ultra-Low-Power Time-Domain Level-Crossing ADC With Adaptive Sampling Rate","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits & Systems II Express Briefs","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Power (physics); Level crossing; Time domain; Sampling (signal processing); Computer science; Statistics; Mathematics; Physics; Telecommunications; Engineering; Computer vision","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005110888,0.0006235746,0.0007156074,0.0004248058,0.001149076,0.0004277819,0.0004392563,0.0003149084,0.00007415246],"category_scores_gemma":[0.000005196608,0.0006241323,0.0001879457,0.000683276,0.000204481,0.0006320181,0.000001058847,0.0006665831,0.00009019393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003216815,"about_ca_system_score_gemma":0.0002448227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000188801,"about_ca_topic_score_gemma":0.00004054264,"domain_scores_codex":[0.9970667,0.0002763082,0.0006822935,0.0007576645,0.0004150528,0.0008019652],"domain_scores_gemma":[0.9983499,0.0002812258,0.0001101218,0.0007794061,0.0001985053,0.0002808569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006393431,0.0001909432,0.000006186975,0.0002060783,0.0004549094,0.00004053394,0.002506549,0.5660726,0.4246748,0.001307533,0.00043672,0.004039255],"study_design_scores_gemma":[0.01271918,0.002943432,0.0008211839,0.01436128,0.001410765,0.0006530667,0.01017929,0.04649469,0.8712329,0.001543199,0.02921342,0.008427542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0471322,0.0003882195,0.9435477,0.000005128701,0.001149068,0.0007778067,0.0002908096,0.0009789966,0.005730091],"genre_scores_gemma":[0.9972705,0.00001394964,0.00010415,0.00009255139,0.0001142378,0.0002549028,0.00001444179,0.0001488408,0.001986442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9501383,"threshold_uncertainty_score":0.999621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009100600582941,"score_gpt":0.2299708073255245,"score_spread":0.2098798013196951,"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."}}