{"id":"W2965627370","doi":"10.1002/cpe.5454","title":"Internet of Things ‐ integrated IR‐UWB technology for healthcare applications","year":2019,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université du Québec à Chicoutimi","funders":"","keywords":"Body area network; Computer science; Wireless; Node (physics); Computer network; Wireless sensor network; Ultra-wideband; Channel (broadcasting); Physical layer; Telecommunications; Electronic engineering; Engineering","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":[0.0003096661,0.0002225133,0.0001465984,0.0002442414,0.0001631323,0.0003871779,0.0003353888,0.0005207193,0.003391799],"category_scores_gemma":[0.0003488519,0.00008691753,0.0001970018,0.0002989048,0.0001461607,0.0005252581,0.0002663666,0.0003561418,0.001191462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468228,"about_ca_system_score_gemma":0.0001934137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001762547,"about_ca_topic_score_gemma":0.0002134998,"domain_scores_codex":[0.9998077,0.00005271948,0.00001277171,0.00002681891,0.00007948265,0.00002061601],"domain_scores_gemma":[0.9998369,0.00004356385,0.00001447951,0.00002090805,0.00007052665,0.00001364409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002868381,0.0001577999,0.002901078,0.0009114563,0.00007145974,0.001029992,0.0003229452,0.008464106,0.2126222,0.04173934,0.02386197,0.7076308],"study_design_scores_gemma":[0.0001083655,0.00196288,0.009830974,0.0004963041,0.0002178182,0.006243745,0.000595165,0.1411747,0.157677,0.05691214,0.6246628,0.0001180863],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07676268,0.02436778,0.74347,0.005815971,0.00239993,0.0003121677,0.0002682654,0.002402983,0.1442003],"genre_scores_gemma":[0.7655243,0.01254382,0.177862,0.002689768,0.0006206641,0.0002120049,0.00046296,0.0001002632,0.0399843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003391799,"threshold_uncertainty_score":0.0113467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471353826214409,"score_gpt":0.2903653833738191,"score_spread":0.275651845111675,"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."}}