{"id":"W3213316963","doi":"10.2196/24172","title":"Personas for Better Targeted eHealth Technologies: User-Centered Design Approach","year":2021,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Persona Design and Applications","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"eHealth; Silhouette; Persona; Computer science; Context (archaeology); Cluster analysis; User-centered design; Set (abstract data type); Process (computing); Human–computer interaction; Iterative and incremental development; Data science; Artificial intelligence; Health care; Geography; Software engineering","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":[0.03968,0.001187089,0.0008730324,0.002866976,0.00177065,0.004465157,0.002325556,0.001333916,0.005462541],"category_scores_gemma":[0.03119333,0.0008283628,0.001551852,0.00137734,0.002578604,0.0035578,0.005282003,0.001879046,0.0009406494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002322055,"about_ca_system_score_gemma":0.003123003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007825252,"about_ca_topic_score_gemma":0.00131884,"domain_scores_codex":[0.9552979,0.03848925,0.001448632,0.001842976,0.002414547,0.0005066317],"domain_scores_gemma":[0.9713112,0.02053808,0.001294534,0.00246792,0.003509328,0.0008789537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001509985,0.002433766,0.01657818,0.008597807,0.0005887187,0.0006603751,0.1458122,0.01278889,0.02373443,0.1107852,0.0103642,0.6661462],"study_design_scores_gemma":[0.003029915,0.009622918,0.02642641,0.00662718,0.001289501,0.002667452,0.1161007,0.1230573,0.04174959,0.2220019,0.4465651,0.0008620775],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04798635,0.0005339968,0.9353254,0.001319511,0.0001101216,0.006165151,0.0002893574,0.0009144609,0.007355696],"genre_scores_gemma":[0.0977961,0.0002264855,0.8927882,0.0002692977,0.00001582103,0.007072004,0.0001577128,0.00009386868,0.001580536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03968,"threshold_uncertainty_score":0.2098504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0888377109385197,"score_gpt":0.313610719949413,"score_spread":0.2247730090108933,"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."}}