{"id":"W4367053414","doi":"10.1101/2023.04.25.537919","title":"A Nanoparticle RIG-I Agonist for Cancer Immunotherapy","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"interferon and immune responses","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vanderbilt Digestive Diseases Research Center, Vanderbilt University Medical Center; Canadian Institutes of Health Research; Vanderbilt Institute of Nanoscale Science and Engineering, Vanderbilt University; Congressionally Directed Medical Research Programs; Vanderbilt University Medical Center; National Science Foundation; Vanderbilt-Ingram Cancer Center; Vanderbilt University","keywords":"Cancer research; Cancer immunotherapy; Tumor microenvironment; Chemistry; Immunotherapy; In vivo; Immunogenicity; Immune system; Pharmacology; Breast cancer; Cancer; Medicine; Internal medicine; Immunology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001332712,0.0003422062,0.0001568749,0.000151824,0.000105975,0.0002526001,0.0001636467,0.0004569172,0.001405532],"category_scores_gemma":[0.00007246681,0.0001034437,0.0002618618,0.00007602313,0.0001350319,0.0001816315,0.000213327,0.0004734245,0.0006466158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003069894,"about_ca_system_score_gemma":0.0001632737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002219061,"about_ca_topic_score_gemma":0.0002605633,"domain_scores_codex":[0.9999139,0.00001667989,0.000005778593,0.00001995558,0.00002738758,0.0000162917],"domain_scores_gemma":[0.999966,0.000005452679,0.000009675594,0.000003910002,0.0000073403,0.000007515681],"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":[0.00004690626,0.00002267034,0.00002769685,0.00005312323,0.00000376009,0.0000250419,0.000006592188,0.0001827984,0.9966518,0.0001657999,0.0001584845,0.002655142],"study_design_scores_gemma":[0.00002292477,0.0005282497,0.0001969021,0.00001083835,0.00001439262,0.0002085017,0.000009256475,0.00186028,0.9887455,0.000103176,0.00829403,0.000006011745],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9018915,0.02156784,0.0526599,0.001557101,0.0005480406,0.0003820684,0.0008352948,0.0007817014,0.01977659],"genre_scores_gemma":[0.9741929,0.002799274,0.01306131,0.0003756279,0.00004008283,0.0001471799,0.0003797698,0.00003166528,0.008972201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001405532,"threshold_uncertainty_score":0.004701972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437281140301148,"score_gpt":0.2628870925377491,"score_spread":0.2385142811347376,"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."}}