{"id":"W4380051178","doi":"10.1038/s44161-023-00278-y","title":"Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis","year":2023,"lang":"en","type":"article","venue":"Nature Cardiovascular Research","topic":"Atherosclerosis and Cardiovascular Diseases","field":"Immunology and Microbiology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institutes of Health; Chan Zuckerberg Initiative; NYU Grossman School of Medicine; Icahn School of Medicine at Mount Sinai; American Heart Association","keywords":"Repurposing; Inflammation; Drug; Drug repositioning; Medicine; Immunology; Pharmacology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007894049,0.0003635489,0.000933991,0.001225706,0.0005395039,0.0001544038,0.000812137,0.001277558,0.00007512433],"category_scores_gemma":[0.001599583,0.000344205,0.001301039,0.003463445,0.0002715891,0.0001518325,0.0003759905,0.002706902,0.001954392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003597283,"about_ca_system_score_gemma":0.0002089695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002511011,"about_ca_topic_score_gemma":0.0000110484,"domain_scores_codex":[0.9933774,0.002946807,0.000525304,0.001083003,0.0007190756,0.001348367],"domain_scores_gemma":[0.9968107,0.0005579462,0.0000623501,0.001933726,0.0005297512,0.0001054634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001477006,0.0007716473,0.0474173,0.001213208,0.01963407,0.0006993976,0.005616829,0.1901172,0.5941314,0.01388484,0.04398918,0.08104791],"study_design_scores_gemma":[0.004864934,0.0002480549,0.1875554,0.002128147,0.0003142608,0.00006275379,0.003354253,0.0003771323,0.09475942,0.0009326854,0.7038649,0.001538131],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8540565,0.1386726,0.001440795,0.0005650218,0.001904802,0.002151592,0.00006854271,0.0005125327,0.0006275682],"genre_scores_gemma":[0.996776,0.001040906,0.0002605948,0.0000822885,0.0002611529,0.0007882614,0.0002320891,0.0001020344,0.0004566622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6598757,"threshold_uncertainty_score":0.999901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03238680894572724,"score_gpt":0.3154326477970542,"score_spread":0.2830458388513269,"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."}}