{"id":"W2150825779","doi":"10.1186/s12955-014-0205-1","title":"Strategies to use tablet computers for collection of electronic patient-reported outcomes","year":2015,"lang":"en","type":"article","venue":"Health and Quality of Life Outcomes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta; Faculty of Nursing, University of Alberta; Canadian Institutes of Health Research; Hartford Foundation for Public Giving; John A. Hartford Foundation","keywords":"Data collection; Electronic data capture; Process (computing); Quality of life (healthcare); Mobile device; Electronic data; Scale (ratio); Mobile technology; Medicine; Psychology; Computer science; Nursing; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002733981,0.0002269967,0.001228103,0.0002426137,0.0005353066,0.000009694253,0.0001244352,0.000177739,0.0000111568],"category_scores_gemma":[0.002289625,0.0001952682,0.0001104564,0.000376183,0.00007437978,0.0001809175,0.00006459613,0.0002890623,0.000005384888],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002510021,"about_ca_system_score_gemma":0.006871938,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01308568,"about_ca_topic_score_gemma":0.002733638,"domain_scores_codex":[0.9949259,0.0007089873,0.002621336,0.0003822846,0.0004021692,0.000959394],"domain_scores_gemma":[0.9932286,0.002422565,0.001639259,0.0004649043,0.0006806093,0.001564109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007086033,0.0001915525,0.9189281,0.003163706,0.00006383644,5.5459e-8,0.004672999,0.00002720068,0.00000970438,0.04530018,0.02459194,0.002342062],"study_design_scores_gemma":[0.005326413,0.00169486,0.7922621,0.0001658166,0.00002543954,6.698688e-7,0.01264261,0.0001432405,0.000006485526,0.002141658,0.185308,0.0002826738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505385,0.000570367,0.0138865,0.0249079,0.0007827687,0.008738362,0.0002243461,0.0001221925,0.0002290504],"genre_scores_gemma":[0.9615057,0.0002869787,0.008436411,0.02622752,0.00005776818,0.002828005,0.0001415079,0.00003566073,0.0004804966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1607161,"threshold_uncertainty_score":0.9987582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2137921979029736,"score_gpt":0.4926868487749229,"score_spread":0.2788946508719493,"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."}}