{"id":"W3211088199","doi":"10.1016/j.clnesp.2021.10.020","title":"Use of digital technologies in the nutritional management of catabolism-prone chronic diseases: A rapid review","year":2021,"lang":"en","type":"review","venue":"Clinical Nutrition ESPEN","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Alberta Innovates","keywords":"Medicine; Catabolism; Intensive care medicine; Bioinformatics; Internal medicine; Metabolism","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001672029,0.0003649352,0.003078574,0.0002375272,0.0002148081,0.00001346125,0.0008698064,0.0006791087,0.0002994784],"category_scores_gemma":[0.001067997,0.0002646972,0.0008338131,0.001395387,0.0003893856,0.0001738353,0.0003718877,0.001590621,0.0001212175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002308205,"about_ca_system_score_gemma":0.00149873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008839401,"about_ca_topic_score_gemma":0.000008746747,"domain_scores_codex":[0.9915662,0.00166799,0.005003127,0.0006986514,0.0004892321,0.0005747561],"domain_scores_gemma":[0.9909232,0.005013518,0.00206874,0.001492401,0.0003308077,0.0001713252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000143269,0.001278742,0.00003182731,0.3252595,0.00004918916,0.000007867565,0.00000413281,1.876735e-8,6.150391e-9,0.006767633,0.04336732,0.6232194],"study_design_scores_gemma":[0.0008244083,0.00008448654,0.00005910284,0.2254776,0.0005269753,0.000003963368,0.0001590209,5.940101e-7,2.4103e-8,0.0007802925,0.7719405,0.0001430806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002619724,0.9750897,0.00003137493,0.003674972,0.0002675699,0.0179439,0.002641894,0.0000702071,0.0002777306],"genre_scores_gemma":[0.00001750977,0.9589535,0.0005336673,0.0004628186,0.0003056087,0.03541248,0.004189842,0.00003770362,0.00008683852],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7285731,"threshold_uncertainty_score":0.9999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2991289814837699,"score_gpt":0.5475026299607212,"score_spread":0.2483736484769513,"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."}}