{"id":"W3042022928","doi":"10.1002/acm2.12958","title":"Capacitive monitoring system for real‐time respiratory motion monitoring during radiation therapy","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen Elizabeth II Health Sciences Centre; Dalhousie University","funders":"Brainlab; Atlantic Canada Opportunities Agency","keywords":"Capacitive sensing; Respiratory monitoring; Continuous monitoring; Computer science; Remote patient monitoring; Motion detection; Breathing; Wearable computer; Radiation monitoring; Acoustics; Biomedical engineering; Materials science; Nuclear medicine; Artificial intelligence; Motion (physics); Physics; Medicine; Engineering; Embedded system; Respiratory system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006228149,0.0004662966,0.000369466,0.0004707912,0.000180318,0.0005027516,0.0009096903,0.0007170363,0.002291654],"category_scores_gemma":[0.001536553,0.0001993585,0.0002433586,0.0003905182,0.0001672678,0.0005754319,0.0004777377,0.0003568444,0.0008874176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002825632,"about_ca_system_score_gemma":0.0002596041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002252361,"about_ca_topic_score_gemma":0.0003399633,"domain_scores_codex":[0.999216,0.0001554728,0.0000440031,0.0001926853,0.0003570244,0.00003493983],"domain_scores_gemma":[0.9992403,0.0002270505,0.0001933869,0.00007395389,0.0002249493,0.0000404594],"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":[0.0003432498,0.00005933616,0.002586418,0.0003762875,0.00003451015,0.0001248258,0.0001091324,0.0007070526,0.8727586,0.0005207275,0.001957942,0.1204218],"study_design_scores_gemma":[0.0002117236,0.003742776,0.03449127,0.0001442657,0.0002575233,0.004075205,0.000157465,0.04758724,0.8538761,0.0007368705,0.0545231,0.000196483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2055276,0.005971912,0.7752456,0.0006262579,0.0009787523,0.0004942908,0.0009736845,0.004115315,0.006066482],"genre_scores_gemma":[0.7986917,0.001820015,0.1922187,0.0007428157,0.0005143202,0.0003797252,0.0005484128,0.0001122587,0.004971937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002291654,"threshold_uncertainty_score":0.007666349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04939662303792026,"score_gpt":0.3078563225429013,"score_spread":0.258459699504981,"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."}}