{"id":"W4393025031","doi":"10.1101/2024.03.19.24304556","title":"Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"National Institutes of Health; National Science Foundation","keywords":"Psychological intervention; Medicine; Precision medicine; Lung cancer; Smoking cessation; Health care; Personalized medicine; Odds; Genome-wide association study; Disease; Lung cancer screening; MEDLINE; Family medicine; Bioinformatics; Oncology; Logistic regression; Internal medicine; Nursing; Pathology; Genotype; Single-nucleotide polymorphism; Biology; Genetics","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":[0.02357125,0.0006984238,0.000966408,0.001535626,0.002609042,0.006600496,0.001645016,0.005868161,0.009444597],"category_scores_gemma":[0.07978649,0.0005127784,0.001245166,0.0009850641,0.004246129,0.004853869,0.007443618,0.008872671,0.002161673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002280419,"about_ca_system_score_gemma":0.008788513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002836649,"about_ca_topic_score_gemma":0.004446292,"domain_scores_codex":[0.9806758,0.01538147,0.0005281944,0.0009071925,0.001662112,0.0008452884],"domain_scores_gemma":[0.9539655,0.03310322,0.002447667,0.002480077,0.002303748,0.005699767],"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":[0.0003773611,0.001782423,0.09634251,0.002006104,0.0007391644,0.001718405,0.02191653,0.003310977,0.002062239,0.03393131,0.2283631,0.6074499],"study_design_scores_gemma":[0.0006479961,0.001355796,0.05689807,0.006651205,0.0009621395,0.001977396,0.0257499,0.006412725,0.00260096,0.4969393,0.3993703,0.000434143],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06517728,0.01031495,0.05066726,0.8440952,0.002182417,0.0004630931,0.0004989286,0.0007850933,0.02581586],"genre_scores_gemma":[0.5807867,0.01715824,0.1645195,0.2281606,0.003801242,0.00113566,0.0005580386,0.0002409164,0.003639072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02357125,"threshold_uncertainty_score":0.1246582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08488138663732005,"score_gpt":0.3568608436885062,"score_spread":0.2719794570511861,"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."}}