{"id":"W4406352829","doi":"10.2196/59485","title":"Building a Decentralized Biobanking App for Research Transparency and Patient Engagement: Participatory Design Study","year":2025,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biobank; Transparency (behavior); Usability; Workflow; Citizen science; Citizen journalism; Computer science; Mindset; Process management; Human–computer interaction; Knowledge management; World Wide Web; Engineering; Bioinformatics","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":[],"consensus_categories":[],"category_scores_codex":[0.00768667,0.0001954455,0.000408495,0.0004999157,0.0007817407,0.0001091152,0.0002699621,0.0002333383,0.0001118349],"category_scores_gemma":[0.00492871,0.0001644004,0.00009614779,0.0004905662,0.0003405579,0.00007079259,0.0001927603,0.001673086,0.000003436655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000218181,"about_ca_system_score_gemma":0.000328485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006498723,"about_ca_topic_score_gemma":0.0000821535,"domain_scores_codex":[0.9958202,0.0008560429,0.0006581027,0.0006618349,0.001209272,0.0007945094],"domain_scores_gemma":[0.989688,0.008926558,0.00006609319,0.0005213048,0.000522291,0.0002757578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002587721,0.007672864,0.7751727,0.002964286,0.001163561,0.0001040153,0.06233942,0.0000236718,0.03619897,0.08202209,0.003926276,0.02582443],"study_design_scores_gemma":[0.0247562,0.01825913,0.6938735,0.003489356,0.0006673745,0.000001639832,0.03262781,0.0005060114,0.04435112,0.1540571,0.02624157,0.001169153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912801,0.0003074131,0.002188786,0.0003629653,0.0001090854,0.005319462,0.000008406211,0.0000937319,0.0003300694],"genre_scores_gemma":[0.9972001,0.00005311281,0.001259954,0.0001115019,0.00003095619,0.001040864,0.000006415411,0.00003157443,0.0002654619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08129918,"threshold_uncertainty_score":0.7268817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8146957606722978,"score_gpt":0.6677049207072846,"score_spread":0.1469908399650132,"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."}}