{"id":"W2029420305","doi":"10.1109/iembs.2011.6090123","title":"Breathing sensor selection during movement","year":2011,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Breathing; Computer science; SIGNAL (programming language); Artificial intelligence; Acoustics; Speech recognition; Pattern recognition (psychology); Physics; Medicine","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":[0.0005823028,0.0005002946,0.0006646494,0.0004883955,0.0002016882,0.0004293403,0.0005019603,0.0007632141,0.001309498],"category_scores_gemma":[0.002887255,0.0002103645,0.0002778932,0.0002402339,0.0001597649,0.0004664126,0.0003561857,0.0003052252,0.0006147291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001308213,"about_ca_system_score_gemma":0.0001657814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002895308,"about_ca_topic_score_gemma":0.0006942145,"domain_scores_codex":[0.9992235,0.0001815896,0.00004118732,0.0002408203,0.0002469067,0.00006593242],"domain_scores_gemma":[0.9992531,0.0002561199,0.00008356845,0.00006973242,0.0002781888,0.00005924997],"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":[0.001189437,0.0001170512,0.009750777,0.0002383263,0.00006987275,0.0002296004,0.0001286228,0.00191537,0.8148925,0.0001692722,0.001133236,0.170166],"study_design_scores_gemma":[0.0001227734,0.001617587,0.145553,0.00005239806,0.0001324652,0.002698436,0.0001408293,0.08894933,0.7557046,0.0005131987,0.004418971,0.00009641524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6970282,0.001482283,0.2942522,0.0003728059,0.0003837338,0.0002430693,0.0004474396,0.001696185,0.004094005],"genre_scores_gemma":[0.9062954,0.0002890933,0.09029523,0.0002214795,0.0000933285,0.0001061278,0.0003021895,0.0001590601,0.002238092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001309498,"threshold_uncertainty_score":0.004380643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01485540677238814,"score_gpt":0.1885920012785181,"score_spread":0.17373659450613,"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."}}