{"id":"W7135169672","doi":"10.5281/zenodo.19006541","title":"Wearable Tech Integration for Remote Patient Monitoring in Nigerian Federal Medical Centers: A Comparative Analysis","year":2013,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Wearable computer; Wearable technology; Health care; Health technology; Remote patient monitoring; Healthcare system","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":[0.00516915,0.0002651784,0.0005249497,0.001771922,0.0007200251,0.001072045,0.0003455397,0.0005763983,0.001412732],"category_scores_gemma":[0.01219138,0.0001885064,0.000618306,0.002999295,0.0004929488,0.0007723171,0.0008610373,0.0002769259,0.0001610062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001675528,"about_ca_system_score_gemma":0.001507328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006282884,"about_ca_topic_score_gemma":0.01395444,"domain_scores_codex":[0.9963397,0.001844862,0.000435404,0.0002712343,0.0007466606,0.0003622351],"domain_scores_gemma":[0.9891423,0.005992171,0.002234868,0.0004313508,0.001857777,0.0003415912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001432294,0.001315158,0.8599643,0.001466419,0.0003104316,0.001101678,0.01139532,0.0006566026,0.00223238,0.0006512153,0.0006909989,0.1187832],"study_design_scores_gemma":[0.00003174973,0.002542622,0.9689426,0.0003563328,0.0002825478,0.001014285,0.02259248,0.000794419,0.001217412,0.00005639257,0.002144006,0.00002504738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981055,0.0005691718,0.0003346113,0.00006267925,0.000004001214,0.00006666714,0.00009491689,0.000003318288,0.0007590445],"genre_scores_gemma":[0.9986351,0.0005754145,0.0004736098,0.00003271559,0.000003809959,0.00005165053,0.00008502181,0.000001752009,0.0001408447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006282884,"threshold_uncertainty_score":0.02733743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06374387647205083,"score_gpt":0.3228849117587705,"score_spread":0.2591410352867197,"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."}}