{"id":"W1993523857","doi":"10.1109/biocas.2011.6107808","title":"An 8-channel readout front-end for long-term sleep quality monitoring","year":2011,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Food Inspection Agency","keywords":"CMOS; Front and back ends; Noise (video); Amplifier; Instrumentation amplifier; Analog front-end; Computer science; Channel (broadcasting); Electrical engineering; Chip; Filter (signal processing); Common-mode rejection ratio; Term (time); Computer hardware; Electronic engineering; Engineering; Operational amplifier; Physics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002791041,0.0001811348,0.0002148329,0.00006032357,0.00007203831,0.00002886381,0.0001985954,0.0001157558,0.000210262],"category_scores_gemma":[0.00001262849,0.0001742686,0.00009213527,0.00004166168,0.00002259592,0.0002478509,0.000008950597,0.0001071361,0.0000867209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004915345,"about_ca_system_score_gemma":0.000008186013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001615308,"about_ca_topic_score_gemma":0.0000504758,"domain_scores_codex":[0.999028,0.00002746002,0.0002526795,0.0002237494,0.0001133485,0.0003548142],"domain_scores_gemma":[0.9994054,0.00004455417,0.00002755564,0.0003075394,0.00005016289,0.0001648111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005927926,0.001348548,0.3018474,0.002523831,0.002050588,0.0002116074,0.02967631,0.008238325,0.207137,0.1486293,0.006250576,0.2914937],"study_design_scores_gemma":[0.003456641,0.0009582133,0.5487228,0.0001949841,0.0003478179,0.0000341149,0.002378803,0.01104403,0.3937506,0.03540987,0.0004117133,0.003290402],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1224312,0.0002523947,0.8605895,8.812819e-7,0.000615304,0.000216021,0.00001238003,0.0005416647,0.01534069],"genre_scores_gemma":[0.998272,0.00001645131,0.0005889513,0.00001352514,0.0003451834,0.00004922475,0.00001516959,0.0000490701,0.0006504254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8758408,"threshold_uncertainty_score":0.7106467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08634515238333502,"score_gpt":0.2880334511265057,"score_spread":0.2016882987431707,"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."}}