{"id":"W4388089028","doi":"10.1136/jitc-2023-sitc2023.0119","title":"119 Uncovering spatial biology of mouse tumor immune microenvironment using imaging mass cytometry","year":2023,"lang":"en","type":"article","venue":"Regular and Young Investigator Award Abstracts","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fluidigm (Canada); Canadian Standards Association","funders":"","keywords":"Mass cytometry; Tumor microenvironment; Immune system; Cancer research; Context (archaeology); Pathology; Medicine; Biology; Immunology; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002781781,0.00024157,0.000286581,0.0001226942,0.0001094868,0.00003172232,0.0001657379,0.0001272506,0.000004529056],"category_scores_gemma":[0.0001021837,0.0002484401,0.0001198505,0.0001369099,0.000325004,0.00001137877,0.0001072372,0.0001284375,0.000005685723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003011233,"about_ca_system_score_gemma":0.0001000553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004677017,"about_ca_topic_score_gemma":0.00001417816,"domain_scores_codex":[0.9985795,0.0000529647,0.0004234671,0.0004197298,0.0001406742,0.0003836732],"domain_scores_gemma":[0.9992466,0.00001280612,0.0001748051,0.00031935,0.00003325587,0.0002131574],"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":[0.00002996575,0.00002614145,0.06292603,0.00007913433,0.00005428457,0.00001280967,0.00004076159,0.0006915162,0.9358162,0.00001429146,0.00005374151,0.0002551535],"study_design_scores_gemma":[0.0005716735,0.00007956023,0.02133873,0.00004950849,0.00003873102,0.000044445,0.00008230961,0.0007219031,0.9749759,0.0001069107,0.001714205,0.0002761259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965293,0.001028218,0.001714815,0.00007614147,0.0003566644,0.0001461994,0.00006322472,0.00003315494,0.00005223003],"genre_scores_gemma":[0.9974982,0.000249376,0.001659129,0.000105913,0.0001587635,0.000004947612,0.0001441749,0.00004812786,0.0001314065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0415873,"threshold_uncertainty_score":0.9999968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232713183653427,"score_gpt":0.2271004150665001,"score_spread":0.2147732832299658,"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."}}