{"id":"W3209320363","doi":"10.1016/j.celrep.2021.109919","title":"Single-cell analysis of the human pancreas in type 2 diabetes using multi-spectral imaging mass cytometry","year":2021,"lang":"en","type":"article","venue":"Cell Reports","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pancreas Centre (Canada)","funders":"National Institute of Allergy and Infectious Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; Juvenile Diabetes Research Foundation United States of America; National Institutes of Health; Leona M. and Harry B. Helmsley Charitable Trust","keywords":"Pancreas; Mass cytometry; Islet; Stromal cell; Immune system; Enteroendocrine cell; Diabetes mellitus; Biology; Cell type; CD8; Type 2 diabetes; Internal medicine; Endocrinology; Flow cytometry; Endocrine system; Immunology; Cell; Medicine; Cancer research; Hormone; Phenotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001828898,0.0001458357,0.0002695593,0.0001131891,0.00006444705,0.00002581151,0.0001120732,0.00009728211,0.00002801416],"category_scores_gemma":[0.00005858083,0.0001299294,0.0002422684,0.0007387964,0.00007002126,0.000004230655,0.00006650188,0.0001096118,2.850275e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003327174,"about_ca_system_score_gemma":0.00009165904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009357344,"about_ca_topic_score_gemma":0.0001118821,"domain_scores_codex":[0.9987516,0.00007221075,0.0004022491,0.0003829908,0.0001394472,0.0002515251],"domain_scores_gemma":[0.9990801,0.00001131041,0.0002124912,0.0005274497,0.0001189866,0.00004961805],"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":[0.000002564413,0.0001238024,0.4225104,0.00001721829,0.00004782795,0.0000454412,0.00002295547,0.0002806029,0.5768954,3.77582e-7,0.000006580649,0.00004690413],"study_design_scores_gemma":[0.0002066075,0.00001800796,0.04755489,0.00001667724,0.0002554456,0.000008284273,0.00005571918,0.000886742,0.9505297,0.00001164222,0.0003040551,0.0001522468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961013,0.001988451,0.0005106381,0.000008780413,0.0002729118,0.00007081035,0.000004642341,0.000006572177,0.001035936],"genre_scores_gemma":[0.998184,0.00003023605,0.001183291,0.00006352161,0.0000530145,0.000001368723,0.00007841189,0.0000229022,0.0003832093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3749555,"threshold_uncertainty_score":0.5298368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02012973432188701,"score_gpt":0.2475161576641293,"score_spread":0.2273864233422423,"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."}}