{"id":"W4380291901","doi":"10.1021/acsnano.3c01645","title":"Multivalent Carbohydrate Nanocomposites for Tumor Microenvironment Remodeling to Enhance Antitumor Immunity","year":2023,"lang":"en","type":"article","venue":"ACS Nano","topic":"Immune cells in cancer","field":"Immunology and Microbiology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Ministry of Science and Technology, Taiwan; National Research Foundation of Korea; Korea Health Industry Development Institute; Swedish Foundation for International Cooperation in Research and Higher Education","keywords":"Tumor microenvironment; Cancer immunotherapy; Adjuvant; Immune system; Cancer research; Immunotherapy; Immunogenicity; Innate immune system; Cytotoxic T cell; Biology; Immunology; Chemistry; Biochemistry; In vitro","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":[0.00006912717,0.000230889,0.0001032902,0.0001386212,0.00006474088,0.000157416,0.000126067,0.0002179778,0.0005094735],"category_scores_gemma":[0.00006300361,0.00007592177,0.0001572349,0.0000868077,0.00008707267,0.0001985017,0.0001734186,0.0002999282,0.000128889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002214031,"about_ca_system_score_gemma":0.0001245673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002380621,"about_ca_topic_score_gemma":0.0004026013,"domain_scores_codex":[0.9999602,0.000005212855,0.000002119715,0.000009605791,0.00001355462,0.00000925903],"domain_scores_gemma":[0.9999777,0.000003329128,0.000006746067,0.000001699701,0.000004400405,0.000006065398],"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":[0.00002914683,0.0000222476,0.00004718012,0.00006328178,0.000004319697,0.00002900278,0.000006450009,0.0003239506,0.9949777,0.0003695408,0.00009142877,0.004035841],"study_design_scores_gemma":[0.00001622857,0.0001854704,0.0005341739,0.00000691957,0.00001932088,0.0001099524,0.00001042556,0.005151929,0.9872268,0.0001515282,0.00657832,0.000009055331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488405,0.007286718,0.03545742,0.0003338017,0.0001636356,0.00009659347,0.0001825365,0.0003658648,0.007272885],"genre_scores_gemma":[0.9867242,0.001461845,0.009500578,0.00009548447,0.00002049177,0.00005492648,0.00007995095,0.00002044182,0.002042074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005094735,"threshold_uncertainty_score":0.001704335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01431555407270928,"score_gpt":0.2745990759635226,"score_spread":0.2602835218908133,"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."}}