{"id":"W3025299331","doi":"10.2196/18412","title":"Optimizing Health Information Technologies for Symptom Management in Cancer Patients and Survivors: Usability Evaluation","year":2020,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Cancer survivorship and care","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Center for Advancing Translational Sciences; National Institute of Mental Health","keywords":"Usability; System usability scale; Medicine; Web usability; Health care; Nursing; Computer science; Human–computer interaction","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":[0.02184592,0.0006232478,0.0006996745,0.001266164,0.0006946735,0.001116331,0.0006043829,0.0006511664,0.001406027],"category_scores_gemma":[0.04567957,0.0002953629,0.001387607,0.0008416661,0.0005272949,0.0009435258,0.001204584,0.0004706878,0.0001864203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000905972,"about_ca_system_score_gemma":0.001797058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001087067,"about_ca_topic_score_gemma":0.001805801,"domain_scores_codex":[0.9884778,0.007932981,0.001523698,0.0003273589,0.001345769,0.0003923145],"domain_scores_gemma":[0.9623948,0.02952317,0.001521728,0.001150444,0.004691675,0.0007183377],"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":[0.01035886,0.03218335,0.1638234,0.01228633,0.001122034,0.0006146943,0.04363037,0.005386292,0.01678742,0.0005302823,0.005022269,0.7082546],"study_design_scores_gemma":[0.008606185,0.1731965,0.6771113,0.004078586,0.004022754,0.001653234,0.03541216,0.02834731,0.03973944,0.001324873,0.02587888,0.0006287712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869618,0.0004353932,0.003919506,0.000167707,0.00002404298,0.006732427,0.000222764,0.0001292652,0.001407149],"genre_scores_gemma":[0.9529312,0.0008435391,0.03483593,0.0001702504,0.00003861662,0.009907224,0.0004963886,0.00004632077,0.0007304251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02184592,"threshold_uncertainty_score":0.1155336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0965389225969275,"score_gpt":0.4485455715647841,"score_spread":0.3520066489678566,"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."}}