{"id":"W4399908809","doi":"10.1109/tbcas.2024.3417716","title":"A 382nVrms 100GΩ@50Hz Active Electrode for Dry-Electrode EEG Recording","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Electrode; Electroencephalography; Materials science; Optoelectronics; Computer science; Electrical engineering; Electronic engineering; Chemistry; Engineering; Psychology; Neuroscience","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":[0.0002512721,0.0006327409,0.000409563,0.0003949538,0.0002137503,0.0005159621,0.001536969,0.0008403683,0.00599269],"category_scores_gemma":[0.0007524241,0.0002491518,0.0002687582,0.0003625597,0.0002531844,0.0008354962,0.0004623104,0.0004509831,0.001977796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002679849,"about_ca_system_score_gemma":0.0001978657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001888489,"about_ca_topic_score_gemma":0.000628533,"domain_scores_codex":[0.9995542,0.00004877127,0.00003641436,0.0001130703,0.0002167257,0.00003071003],"domain_scores_gemma":[0.999615,0.0001051085,0.00005556143,0.00005779591,0.0001312559,0.00003535865],"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":[0.0001560601,0.00004108113,0.0004738207,0.0003177057,0.00002835465,0.0002994875,0.00005946595,0.000241389,0.9217413,0.001119474,0.002958518,0.07256345],"study_design_scores_gemma":[0.0001603703,0.002123609,0.01354608,0.000106762,0.0002110842,0.006148088,0.0001062601,0.01942851,0.8566668,0.001273811,0.1001515,0.00007717286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0814185,0.002068753,0.9002922,0.0006773706,0.0006632955,0.0004606671,0.001067595,0.004243685,0.009107906],"genre_scores_gemma":[0.5006122,0.00113646,0.4805965,0.0009463268,0.0003199934,0.000423213,0.0009101395,0.0002963612,0.01475888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00599269,"threshold_uncertainty_score":0.02004749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03741926060997224,"score_gpt":0.2796009316830816,"score_spread":0.2421816710731093,"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."}}