{"id":"W4392558563","doi":"10.1016/j.jmb.2024.168522","title":"A Commentary on Multi-omics Data Integration in Systems Vaccinology","year":2024,"lang":"en","type":"article","venue":"Journal of Molecular Biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; Centre for Social Innovation; University of British Columbia; Simon Fraser University; Prevention of Organ Failure","funders":"","keywords":"Omics; Data integration; Computer science; Data science; Computational biology; Data mining; Bioinformatics; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004302275,0.0001485733,0.0002377626,0.0001907664,0.00001972669,0.00003008399,0.0004464923,0.000252815,0.000003673042],"category_scores_gemma":[0.00008485994,0.0001205734,0.0000886741,0.00009387524,0.0000491417,0.000007087006,0.0000929024,0.0003175937,0.000004273628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003671705,"about_ca_system_score_gemma":0.000075084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005129519,"about_ca_topic_score_gemma":0.00005219112,"domain_scores_codex":[0.9987974,0.0002165442,0.0004506669,0.0002799035,0.00006603519,0.0001894924],"domain_scores_gemma":[0.9993932,0.00003044853,0.0001103779,0.0003546155,0.00005902797,0.0000523623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002096066,0.0001505488,0.001292684,0.00002265095,0.0001144038,0.0001372478,0.00003489886,0.0003529952,0.9874911,0.0004255534,0.003001188,0.006767066],"study_design_scores_gemma":[0.007075451,0.008068792,0.00166493,0.0007519929,0.0002611604,0.001643809,0.000464589,0.03672962,0.7351388,0.0008967466,0.2061561,0.001148027],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8768784,0.009715877,0.1087236,0.002177162,0.002173623,0.0001725112,0.0000739137,0.000009263851,0.0000756427],"genre_scores_gemma":[0.9955364,0.0007118917,0.001528155,0.001517432,0.0003439986,0.000002760107,0.0003160746,0.00002271719,0.00002056912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2523524,"threshold_uncertainty_score":0.4916841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03435928785527783,"score_gpt":0.3081385954355835,"score_spread":0.2737793075803057,"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."}}