{"id":"W3093674579","doi":"10.2196/14326","title":"Developing the Accuracy of Vital Sign Measurements Using the Lifelight Software Application in Comparison to Standard of Care Methods: Observational Study Protocol","year":2020,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Vital signs; Health care; Observational study; Data collection; Software; Protocol (science); Computer science; Gold standard (test); Medicine; Medical physics; Data mining; Statistics; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002338602,0.0001864578,0.0003520935,0.0001427866,0.0001719409,0.00007956351,0.0008501437,0.0000637594,0.000005748306],"category_scores_gemma":[0.001217294,0.0001293274,0.00005308089,0.001555537,0.00007206646,0.0002185629,0.0003608795,0.0005035563,0.000003431452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004690646,"about_ca_system_score_gemma":0.0003642527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003889852,"about_ca_topic_score_gemma":0.00003966287,"domain_scores_codex":[0.9962673,0.0008615858,0.000730544,0.0002976876,0.001462834,0.0003801088],"domain_scores_gemma":[0.9975097,0.0008511505,0.0001459755,0.000431037,0.0009695967,0.00009252079],"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":[0.001356972,0.0002820432,0.4515397,0.004260509,0.0001119148,0.000002631954,0.02110506,0.02975048,0.4679912,0.0001208918,0.0002839575,0.02319465],"study_design_scores_gemma":[0.002832426,0.001921397,0.02997984,0.002854721,0.000006948429,5.514446e-7,0.01288036,0.001755686,0.9385231,0.0002230061,0.008606701,0.0004152855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.007060491,0.00000413815,0.1304952,0.0001320719,0.000005951084,0.8622182,0.0000112403,0.00004862,0.00002404005],"genre_scores_gemma":[0.1294628,3.21003e-8,0.03232141,0.00001009073,0.00009491375,0.8380723,0.000001764848,0.00003621957,4.999808e-7],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.4705319,"threshold_uncertainty_score":0.5273817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6103078637252572,"score_gpt":0.5995777329339681,"score_spread":0.01073013079128915,"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."}}