{"id":"W2918817626","doi":"10.1038/s41746-019-0087-z","title":"A computer vision system for deep learning-based detection of patient mobilization activities in the ICU","year":2019,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Intensive Care Unit Cognitive Disorders","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canada Excellence Research Chairs, Government of Canada; Intermountain Healthcare","keywords":"Artificial intelligence; Computer science; Mobilization; Deep learning; Computer vision; Human–computer interaction; Physical medicine and rehabilitation; Medicine; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006811081,0.0007969334,0.0005658509,0.000974833,0.0003240035,0.0005584736,0.001143593,0.0009024431,0.002436894],"category_scores_gemma":[0.001542693,0.0002857955,0.0004591965,0.0006196287,0.000169179,0.000451875,0.0006682854,0.001020877,0.001116611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008109137,"about_ca_system_score_gemma":0.001023283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008938496,"about_ca_topic_score_gemma":0.01050055,"domain_scores_codex":[0.9996424,0.00005020217,0.000027924,0.000127909,0.00008474667,0.00006687863],"domain_scores_gemma":[0.9996895,0.00009409778,0.00003297675,0.00002472704,0.0001215067,0.00003715166],"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":[0.0006480298,0.00119367,0.008088207,0.0002590277,0.0001878678,0.0004016089,0.00007848362,0.04879415,0.04232452,0.0007585193,0.01959512,0.8776708],"study_design_scores_gemma":[0.00006549162,0.0003388782,0.007330238,0.00003057106,0.00003943453,0.000241784,0.00002263412,0.9715288,0.01662821,0.0008420401,0.002900117,0.0000318787],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.210858,0.001608288,0.7562881,0.000629024,0.0004657156,0.0009087727,0.002914795,0.02089469,0.00543264],"genre_scores_gemma":[0.6418652,0.0004837778,0.3468699,0.0007933663,0.0001002211,0.0008792822,0.003376041,0.00018423,0.005448002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008938496,"threshold_uncertainty_score":0.01777291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006485007394866809,"score_gpt":0.2412217533211034,"score_spread":0.2347367459262366,"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."}}