{"id":"W2143516309","doi":"10.1109/mcom.2012.6122530","title":"A wireless wearable ECG sensor for long-term applications","year":2012,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":410,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Wearable computer; Capacitive sensing; Wireless; Wireless sensor network; Real-time computing; Computer hardware; Embedded system; SIGNAL (programming language); Signal conditioning; Power (physics); Telecommunications; Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001621994,0.000155776,0.0001844088,0.00006964793,0.0002232794,0.00003865735,0.0004733081,0.00006988004,0.00003321787],"category_scores_gemma":[0.00002110827,0.0001686232,0.00005616517,0.0001771036,0.00007728317,0.0002411001,0.00005373731,0.000108688,0.0002992185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006073467,"about_ca_system_score_gemma":0.000008690034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002621562,"about_ca_topic_score_gemma":0.00001843815,"domain_scores_codex":[0.9991392,0.00003312007,0.0002683567,0.0001085717,0.00006620528,0.0003844978],"domain_scores_gemma":[0.9981928,0.0001963308,0.00004928414,0.001356669,0.00007957687,0.0001253335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003499953,0.0007155782,0.00697143,0.000733989,0.0002940723,8.690463e-7,0.0005515193,0.03166996,0.8740006,0.01006695,0.009064659,0.06589535],"study_design_scores_gemma":[0.002695704,0.00009207739,0.02922826,0.0003608691,0.0004090671,0.0001296877,0.0001024278,0.06030429,0.1399055,0.001703346,0.7626567,0.002412057],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1778008,0.005216332,0.7870762,0.0004762791,0.001488517,0.001585369,0.000203836,0.002247264,0.02390539],"genre_scores_gemma":[0.9478732,0.000921254,0.04771051,0.0000525176,0.0003582895,0.001007745,0.00014151,0.00008028478,0.001854709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7700723,"threshold_uncertainty_score":0.6876256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03818013121915005,"score_gpt":0.2875852971806729,"score_spread":0.2494051659615228,"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."}}