{"id":"W4410583792","doi":"10.1109/tbcas.2025.3570264","title":"Energy-Efficient Adaptive Neural Stimulator With Waveform Prediction by Sub-Threshold Interrogation of the Electrode-Tissue Interface","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Waveform; Electrode; Interface (matter); Energy (signal processing); Interrogation; Electronic engineering; Computer science; Materials science; Acoustics; Electrical engineering; Voltage; Physics; Engineering","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":[0.0001603878,0.0002296956,0.0001486073,0.0001272949,0.00008326029,0.0002299812,0.0006343473,0.000231688,0.001373811],"category_scores_gemma":[0.0004504834,0.000127073,0.0001348744,0.0001064296,0.0001237626,0.0003398022,0.0003846419,0.0002795287,0.0003318267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143665,"about_ca_system_score_gemma":0.0002004667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004692426,"about_ca_topic_score_gemma":0.001408207,"domain_scores_codex":[0.999921,0.000009937183,0.000004287548,0.00002069567,0.00003825166,0.000005892158],"domain_scores_gemma":[0.999897,0.00004626588,0.00001585468,0.00001476835,0.00001854903,0.000007454873],"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":[0.0002995373,0.0001019553,0.001283805,0.0001139215,0.00003768193,0.0001556569,0.0001071677,0.08560729,0.56156,0.002500458,0.002249141,0.3459834],"study_design_scores_gemma":[0.00001436884,0.0001054486,0.001089153,0.000007241792,0.00001306751,0.0001598945,0.00001209674,0.8821924,0.1126657,0.001348621,0.002377643,0.00001445674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06052773,0.0002131951,0.9356157,0.0001566622,0.00003150079,0.00003489115,0.00007162286,0.001418202,0.001930535],"genre_scores_gemma":[0.6614571,0.0001979006,0.3328165,0.0001795977,0.00002285668,0.00009179794,0.00015191,0.0001739404,0.004908415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001373811,"threshold_uncertainty_score":0.004595816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153704994702085,"score_gpt":0.2409994995624516,"score_spread":0.2256290000922431,"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."}}