{"id":"W4388538575","doi":"10.3389/fimmu.2023.1259197","title":"Baseline gene signatures of reactogenicity to Ebola vaccination: a machine learning approach across multiple cohorts","year":2023,"lang":"en","type":"article","venue":"Frontiers in Immunology","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo; U.S. Department of Health and Human Services","keywords":"Reactogenicity; Medicine; Adverse effect; Vaccination; myalgia; Immunology; Internal medicine; Immunogenicity; Immune system","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":[0.002073052,0.0003322563,0.0005683635,0.000825503,0.0002990185,0.0005995293,0.0002690491,0.0003844452,0.0007952307],"category_scores_gemma":[0.002400859,0.0001304205,0.0005918031,0.0007672756,0.0003058509,0.0002524932,0.0004050879,0.0005447551,0.0001691186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002776381,"about_ca_system_score_gemma":0.0002904501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001494374,"about_ca_topic_score_gemma":0.001331336,"domain_scores_codex":[0.9992685,0.0002771878,0.00003986856,0.0002584744,0.00007593685,0.00008005857],"domain_scores_gemma":[0.9987296,0.0005710859,0.0003564401,0.0001612263,0.00009402321,0.00008757535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001112018,0.0001289538,0.9728255,0.00003035088,0.0004619827,0.00006087977,0.00007729958,0.002597905,0.007681948,0.000047254,0.0002858125,0.01468999],"study_design_scores_gemma":[0.00002585074,0.0005087581,0.9810524,0.00001368049,0.0002110525,0.0001572671,0.0001145486,0.0155399,0.001653236,0.0002799217,0.0004297808,0.00001361235],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958615,0.000236157,0.00258611,0.0000720895,0.000009264287,0.00002818745,0.0009704691,0.00002301251,0.000213217],"genre_scores_gemma":[0.9970859,0.00005719729,0.001391652,0.00003652379,0.00001121532,0.00003972325,0.001255894,0.000005991615,0.000116058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002073052,"threshold_uncertainty_score":0.01096344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087714520657906,"score_gpt":0.3103413124908113,"score_spread":0.2894641672842322,"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."}}