{"id":"W1986943801","doi":"10.2196/resprot.2547","title":"Designing eHealth that Matters via a Multidisciplinary Requirements Development Approach","year":2013,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Persona Design and Applications","field":"Computer Science","cited_by":300,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"eHealth; Multidisciplinary approach; Computer science; Context (archaeology); Domain (mathematical analysis); Quality (philosophy); Knowledge management; Process management; Identification (biology); Risk analysis (engineering); Engineering management; Engineering; Health care; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001702478,0.0001901985,0.0001751657,0.000276966,0.0008302237,0.0005426245,0.001824284,0.00008465195,0.00005383061],"category_scores_gemma":[0.00001253866,0.0001632087,0.0000453441,0.0007582593,0.0001282786,0.0009260983,0.0009220369,0.0004438685,0.0012055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000277905,"about_ca_system_score_gemma":0.0003917438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004013403,"about_ca_topic_score_gemma":0.000001197271,"domain_scores_codex":[0.9963939,0.0004173459,0.0003151406,0.0007222212,0.001162406,0.0009889649],"domain_scores_gemma":[0.9983015,0.0001211208,0.00009310516,0.0008848528,0.0002157941,0.0003836134],"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":[0.000111617,0.00550779,0.01068914,0.001940149,0.0001023181,0.0000427814,0.02207421,0.00004129126,0.2733065,0.00898117,0.2726533,0.4045497],"study_design_scores_gemma":[0.009617089,0.00233143,0.08665627,0.004784192,0.000003580236,0.0001781944,0.002924921,0.2018311,0.1347852,0.02492028,0.5280889,0.003878971],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.0002480573,0.000002466596,0.6027585,0.002672015,0.0000039442,0.3924615,5.462873e-7,0.0001910917,0.001661878],"genre_scores_gemma":[0.007299367,1.794715e-7,0.2708097,0.0001971981,0.00002820349,0.7208912,0.000004198327,0.00001646934,0.0007534947],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.4006708,"threshold_uncertainty_score":0.9995722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3822283938175347,"score_gpt":0.509520806283915,"score_spread":0.1272924124663803,"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."}}