{"id":"W4386946844","doi":"10.1101/2023.09.20.558571","title":"Tumor sialylation controls effective anti-cancer immunity in breast cancer","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Bundesministerium für Bildung, Wissenschaft und Forschung; Österreichischen Akademie der Wissenschaften; Austrian Science Fund; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Cancer; Immunity; Breast cancer; Medicine; Oncology; Cancer research; Internal medicine; Immunology; 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":[0.0001073497,0.0002158971,0.0001857528,0.0001360155,0.00009490548,0.000289546,0.00009696956,0.000178072,0.001473937],"category_scores_gemma":[0.00007106635,0.000102874,0.0001347024,0.000124711,0.0001641216,0.000133376,0.0002497739,0.0002913142,0.0005318223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002390168,"about_ca_system_score_gemma":0.0001666561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002373373,"about_ca_topic_score_gemma":0.0002720947,"domain_scores_codex":[0.9999371,0.000009652016,0.000003686244,0.00001057357,0.00001997438,0.00001897649],"domain_scores_gemma":[0.9999704,0.000003440873,0.000007839142,0.000005749335,0.00000391655,0.00000856067],"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":[0.0001026005,0.00001531558,0.0003598082,0.00002399424,0.000003203753,0.00002698182,0.000006097249,0.0001644367,0.996326,0.000310751,0.00009493635,0.002565832],"study_design_scores_gemma":[0.00001916484,0.0001634484,0.003877986,0.000004943884,0.000007309751,0.0002205055,0.00001917874,0.001888723,0.9874558,0.0005574527,0.005782191,0.000003263083],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851453,0.003596242,0.006020191,0.0002123087,0.00006080821,0.0000313331,0.0004390724,0.0001700221,0.004324725],"genre_scores_gemma":[0.9943945,0.001050528,0.001835925,0.00004456097,0.00001125483,0.00001348013,0.0003661486,0.00003079045,0.00225276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001473937,"threshold_uncertainty_score":0.004930794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01329626531868751,"score_gpt":0.2721366378769089,"score_spread":0.2588403725582214,"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."}}