{"id":"W4207076624","doi":"10.2196/30523","title":"Requirements for a Bespoke Intensive Care Unit Dashboard in Response to the COVID-19 Pandemic: Semistructured Interview Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; University of Bristol; National Institute for Health and Care Research; UK Research and Innovation","keywords":"Dashboard; Bespoke; Pandemic; Medicine; Medical emergency; Coronavirus disease 2019 (COVID-19); Computer science; Business; Data science; Disease","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":[0.000989982,0.0002015644,0.0003552464,0.0003743606,0.0005564995,0.00001181801,0.0003678545,0.0001012322,0.0001112808],"category_scores_gemma":[0.001188495,0.0001538035,0.00008768171,0.0004514452,0.00005067927,0.00003187842,0.0003236146,0.0006618571,0.000003235711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009938746,"about_ca_system_score_gemma":0.0002252209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002259968,"about_ca_topic_score_gemma":0.000830654,"domain_scores_codex":[0.9978856,0.0006022492,0.0004203474,0.0004012571,0.0003370537,0.0003534629],"domain_scores_gemma":[0.9985763,0.0002931515,0.0001177522,0.0005751768,0.0002350259,0.0002026253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001591889,0.00008274671,0.8990833,0.0001509173,0.0000497065,0.00004571069,0.09575272,0.00001505831,0.0008899282,0.000007227356,0.001033399,0.001297422],"study_design_scores_gemma":[0.004146822,0.005848627,0.5047116,0.0001154435,0.00006665695,0.0000243036,0.3317527,0.000002622457,0.0001879537,0.00006140618,0.1528016,0.0002803228],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924359,0.000114948,0.000009459851,0.002413749,0.0003950426,0.004347297,0.0001001589,0.000168398,0.0000150033],"genre_scores_gemma":[0.9945074,0.000001404555,0.00001150086,0.003527252,0.00005283064,0.001408728,0.0001033945,0.00002901039,0.0003584784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3943717,"threshold_uncertainty_score":0.6271924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.291981568504361,"score_gpt":0.4772416431287616,"score_spread":0.1852600746244006,"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."}}