{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002416513,0.0001940488,0.0002334185,0.0005317504,0.0002068165,0.000415926,0.0001598433,0.0003668163,0.0006420522],"category_scores_gemma":[0.0001962382,0.0001037313,0.0001534292,0.000447127,0.0001873097,0.0001745007,0.0002640173,0.0003608472,0.000271426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290626,"about_ca_system_score_gemma":0.000109648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003727404,"about_ca_topic_score_gemma":0.0005253259,"domain_scores_codex":[0.9998945,0.00001345271,0.000009116126,0.00004033855,0.0000295425,0.00001306166],"domain_scores_gemma":[0.9999033,0.00002704239,0.00001700027,0.0000143002,0.00002337248,0.00001487545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004723551,0.00001012412,0.001461676,0.00002221525,0.000004174974,0.00002892079,0.00002950197,0.0001177365,0.9955238,0.00005495576,0.00003214617,0.002667586],"study_design_scores_gemma":[0.00001924284,0.0002014513,0.06706917,0.00002148988,0.00004369993,0.0006985811,0.0002476105,0.01134738,0.9152762,0.0006104457,0.004443065,0.00002165029],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8895693,0.002858355,0.1024399,0.0001584037,0.00005970172,0.0001163634,0.001792564,0.0003601759,0.002645192],"genre_scores_gemma":[0.8774832,0.002725558,0.1154933,0.0002378132,0.00003988531,0.0002811922,0.001703224,0.000076176,0.001959547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006420522,"threshold_uncertainty_score":0.002147913,"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."}}