{"id":"W2799696324","doi":"10.5539/cis.v11n2p99","title":"The Impact of Mobile Application Support on the Quality of Care of Kidney Patients","year":2018,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Adaptation (eye); Quality (philosophy); Dialysis; Intensive care medicine; Medicine; Surgery; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002620201,0.0001783568,0.0002582343,0.0005370895,0.0004084214,0.001218181,0.0002828902,0.0004618565,0.002633432],"category_scores_gemma":[0.02774849,0.00007818913,0.0004953827,0.0004834687,0.0002014205,0.0005985444,0.0008336886,0.0004777354,0.0002621349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000528364,"about_ca_system_score_gemma":0.001114675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002039973,"about_ca_topic_score_gemma":0.002199585,"domain_scores_codex":[0.9967054,0.001870506,0.0001959903,0.0001379904,0.0007570933,0.0003330735],"domain_scores_gemma":[0.980298,0.01239333,0.001735786,0.0004065725,0.002854086,0.002312282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003372597,0.003304596,0.465567,0.000959791,0.0003841916,0.0006902275,0.003087283,0.00179819,0.003955453,0.0004349793,0.004335122,0.5121105],"study_design_scores_gemma":[0.000355454,0.01243479,0.959904,0.0004569045,0.0004769063,0.0006599672,0.005553117,0.007866307,0.002866426,0.0004158731,0.008927744,0.00008242949],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936355,0.0007359883,0.0004135475,0.0009851439,0.00005630151,0.00007670212,0.00009905717,0.000050627,0.003947086],"genre_scores_gemma":[0.9988428,0.0001717319,0.0005056152,0.00009744008,0.00002225871,0.00002316803,0.00004252054,0.00000403046,0.0002903657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002633432,"threshold_uncertainty_score":0.01385713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03618196078524873,"score_gpt":0.4586072345558039,"score_spread":0.4224252737705552,"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."}}