{"id":"W3129038531","doi":"10.3389/fgene.2021.633731","title":"Welfare Genome Project: A Participatory Korean Personal Genome Project With Free Health Check-Up and Genetic Report Followed by Counseling","year":2021,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Korea Research Environment Open Network; Ulsan Metropolitan City; Korea Institute of Science and Technology Information; Korea Institute of Science and Technology; Ulsan National Institute of Science and Technology","keywords":"Personal genomics; Genetic counseling; Health care; Personalized medicine; Public health; Genomics; Genetic testing; Medicine; Genome; Genetics; Nursing; Biology; Political science","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":[0.03076589,0.001044899,0.0007643335,0.001639971,0.005670497,0.002253823,0.00263802,0.001608245,0.009349785],"category_scores_gemma":[0.0136673,0.0009630807,0.0009977752,0.002078311,0.001739008,0.002014889,0.01343175,0.002571497,0.00201445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0029609,"about_ca_system_score_gemma":0.02672246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02402047,"about_ca_topic_score_gemma":0.03020929,"domain_scores_codex":[0.9873397,0.009278426,0.0004166356,0.001278564,0.0005824851,0.001104094],"domain_scores_gemma":[0.9879997,0.002244854,0.0007313564,0.002603093,0.00206779,0.004353027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005730099,0.01371796,0.1310018,0.003334354,0.0008779161,0.003986743,0.04914389,0.001548315,0.01805033,0.0191247,0.2509631,0.5025208],"study_design_scores_gemma":[0.007852974,0.005604505,0.2454211,0.002047376,0.0009081831,0.001696461,0.06242035,0.002871954,0.008324059,0.02044607,0.6418939,0.0005130777],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5048982,0.002769089,0.1547994,0.03547173,0.002402046,0.1598999,0.07870864,0.00278548,0.05826558],"genre_scores_gemma":[0.4322372,0.0020054,0.3064848,0.01651965,0.0002832139,0.1724389,0.03880334,0.0009645011,0.03026287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03076589,"threshold_uncertainty_score":0.1627075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123002488999861,"score_gpt":0.2630591588149664,"score_spread":0.2418291339249678,"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."}}