{"id":"W4236144548","doi":"10.2196/preprints.34567","title":"Cocreating a Harmonized Living Lab for Big Data–Driven Hybrid Persona Development: Protocol for Cocreating, Testing, and Seeking Consensus (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Centre for Interdisciplinary Research in Rehabilitation","funders":"","keywords":"Living lab; Protocol (science); Context (archaeology); Preprint; Health care; Independent living; Workflow; Knowledge management; Computer science; Data science; World Wide Web; Medicine; Political science; Gerontology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1847761,0.002609124,0.003393566,0.006029535,0.006378818,0.006718205,0.004924094,0.006089306,0.09751692],"category_scores_gemma":[0.246846,0.004640015,0.004472533,0.005190067,0.006272782,0.005219552,0.01011937,0.008386943,0.037464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008530039,"about_ca_system_score_gemma":0.04936503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003273697,"about_ca_topic_score_gemma":0.005347447,"domain_scores_codex":[0.8459628,0.1124719,0.01993241,0.006594593,0.01108654,0.003951753],"domain_scores_gemma":[0.7271011,0.1276395,0.01244974,0.06190676,0.06523615,0.005666737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01645032,0.005134349,0.002892493,0.0675002,0.0006941982,0.002570867,0.06621256,0.005576612,0.008213705,0.08073107,0.4114274,0.3325963],"study_design_scores_gemma":[0.01480301,0.003141076,0.005592291,0.03405173,0.0002677028,0.0005097404,0.01797343,0.003524232,0.007742028,0.02593273,0.8858989,0.0005630393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.00123241,0.0001529514,0.02390775,0.0006545426,0.0005032619,0.9665441,0.003885778,0.0003145331,0.002804717],"genre_scores_gemma":[0.0005906221,0.00006711654,0.01046065,0.0001658518,0.00002007807,0.9877638,0.0004170467,0.00003221051,0.0004825568],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.1847761,"threshold_uncertainty_score":0.9772012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1722897563708483,"score_gpt":0.3174523689308212,"score_spread":0.1451626125599729,"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."}}