{"id":"W3213677569","doi":"10.2196/34567","title":"Cocreating a Harmonized Living Lab for Big Data–Driven Hybrid Persona Development: Protocol for Cocreating, Testing, and Seeking Consensus","year":2021,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Persona Design and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Centre for Interdisciplinary Research in Rehabilitation","funders":"European Commission","keywords":"Living lab; Context (archaeology); Protocol (science); Knowledge management; Health care; Independent living; Computer science; World Wide Web; Medicine; Gerontology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1949004,0.003272174,0.00338039,0.006142841,0.007522077,0.006867335,0.006193407,0.007619054,0.05525172],"category_scores_gemma":[0.2159481,0.004336483,0.004510814,0.005633373,0.007352829,0.005799004,0.01056097,0.009991481,0.02286546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01009702,"about_ca_system_score_gemma":0.05355865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00338161,"about_ca_topic_score_gemma":0.005551141,"domain_scores_codex":[0.8394316,0.1210851,0.01831761,0.00648044,0.009861167,0.004823981],"domain_scores_gemma":[0.7439847,0.1110878,0.01255344,0.06399246,0.06171709,0.00666453],"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":[0.01900681,0.009150095,0.003865953,0.0669211,0.0006799455,0.004474679,0.1222051,0.008158942,0.0134772,0.1140023,0.2403678,0.3976901],"study_design_scores_gemma":[0.01823679,0.004488206,0.005875338,0.03456383,0.0003226997,0.0007971051,0.0280938,0.006630467,0.01138153,0.04308359,0.845789,0.0007376306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.001546189,0.0001233417,0.02579277,0.0005169213,0.0002471813,0.9676335,0.001669351,0.0002406934,0.002230064],"genre_scores_gemma":[0.0007543106,0.00006789457,0.01454435,0.0001359924,0.0000127133,0.9838616,0.000255286,0.00002427178,0.0003436336],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1949004,"threshold_uncertainty_score":0.9928312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5718250468072794,"score_gpt":0.5289214499431985,"score_spread":0.04290359686408096,"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."}}