{"id":"W4414833882","doi":"10.17975/sfj-2025-015","title":"Empowering Precision Medicine: Leveraging Multi-Omics Data, Machine Learning Approaches, and Generative AI","year":2025,"lang":"en","type":"article","venue":"STEM Fellowship Journal","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Generative grammar; Precision medicine; Leverage (statistics); Health care; Data integration; Big data","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":[0.001722689,0.0002112786,0.0002463924,0.0001627828,0.0003839495,0.0001431314,0.0005380331,0.0001867963,0.00001404504],"category_scores_gemma":[0.0004493726,0.0001624346,0.00005191583,0.0001333389,0.0002405869,0.00001911329,0.0007069284,0.0006779812,0.000003891855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003375883,"about_ca_system_score_gemma":0.000185406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001395198,"about_ca_topic_score_gemma":0.00002944295,"domain_scores_codex":[0.9982668,0.0001856433,0.0004410178,0.0003683671,0.0003504798,0.0003876933],"domain_scores_gemma":[0.9990444,0.00005643247,0.0001400257,0.0003797146,0.0001364366,0.00024305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007520376,0.0003080465,0.06143379,0.0007145953,0.001039328,0.00007620352,0.004878242,0.001780192,0.2409961,0.0001821445,0.02628572,0.6615536],"study_design_scores_gemma":[0.008874734,0.00158785,0.005980835,0.000877172,0.0002147949,0.0005967739,0.01035967,0.4861427,0.06328756,0.00064402,0.4201527,0.001281202],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3985533,0.02486034,0.5632492,0.007172443,0.001725049,0.0007065951,0.00006158234,0.00004075205,0.003630823],"genre_scores_gemma":[0.9784861,0.005618215,0.009035384,0.0007666294,0.0007303794,0.00000536367,0.0003101248,0.00003070943,0.005017141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6602724,"threshold_uncertainty_score":0.6623889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07124798426306524,"score_gpt":0.3433970844242404,"score_spread":0.2721491001611752,"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."}}