{"id":"W2988438918","doi":"10.22215/etd/2019-13618","title":"Non-Contact Bed-Based Monitoring of Vital Signs","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; AGE-WELL","keywords":"Vital signs; Computer science; SIGNAL (programming language); Artificial intelligence; Computer vision; Segmentation; Real-time computing; Medicine; Surgery","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":[0.000371226,0.0002940272,0.000256055,0.0004414353,0.0002241724,0.0007366244,0.0003923203,0.000324127,0.02351079],"category_scores_gemma":[0.000941594,0.0000915166,0.0001802302,0.0004371746,0.0001252465,0.0002495131,0.000416229,0.000388406,0.01180396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001593861,"about_ca_system_score_gemma":0.0004893706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002586357,"about_ca_topic_score_gemma":0.000486512,"domain_scores_codex":[0.9996088,0.00005870828,0.00001185394,0.0000661156,0.0002256103,0.00002905666],"domain_scores_gemma":[0.999662,0.00008401748,0.00002582554,0.00002691711,0.0001605591,0.00004067409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005274725,0.0005225135,0.002411989,0.001948955,0.0000258666,0.0001428441,0.0008309672,0.0006875892,0.2162365,0.003294904,0.04115093,0.7322196],"study_design_scores_gemma":[0.0001689329,0.004993219,0.1082819,0.001291534,0.0001029256,0.001555578,0.001323716,0.006536328,0.1849477,0.005297178,0.6853941,0.0001069639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2469944,0.03961327,0.1872449,0.002921076,0.004281212,0.002250807,0.006418829,0.0031203,0.5071552],"genre_scores_gemma":[0.4209163,0.02408119,0.0560118,0.00079439,0.001013608,0.001037447,0.003635867,0.0003458894,0.4921636],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02351079,"threshold_uncertainty_score":0.07865143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00995657171358071,"score_gpt":0.2363151299069378,"score_spread":0.226358558193357,"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."}}