{"id":"W4313446325","doi":"10.1007/978-1-0716-2914-7_1","title":"Imaging Mass Cytometry in Immuno-Oncology","year":2023,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Multiplex; Mass cytometry; Workflow; Flow cytometry; Pathology; Cytometry; Computational biology; Medicine; Computer science; Biology; Bioinformatics; 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":[0.001845665,0.0002384808,0.0003833837,0.0005121962,0.00003834427,0.00001332266,0.0004037821,0.0004074998,0.00002136693],"category_scores_gemma":[0.0004517492,0.0002488375,0.0001357628,0.0008347333,0.0001815541,0.000003144582,0.0001755211,0.0002848074,0.00001810409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006447052,"about_ca_system_score_gemma":0.00009998554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009269578,"about_ca_topic_score_gemma":0.00005521545,"domain_scores_codex":[0.9970136,0.001203897,0.0004610964,0.0006283754,0.00006657932,0.0006264786],"domain_scores_gemma":[0.9992573,0.0001089554,0.00007907429,0.000449461,0.00004027554,0.00006494982],"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":[0.0000785908,0.00005286753,0.0370955,0.00001252881,0.00002184836,0.0001066037,0.00005149885,0.0001126268,0.9298639,0.0002677458,0.00005741914,0.03227882],"study_design_scores_gemma":[0.001785548,0.0002991632,0.004873177,0.00002000312,0.00001244142,0.00003668988,0.000180101,0.001350201,0.9478914,0.005214389,0.03784983,0.000487103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2855907,0.001753855,0.7086392,0.0003895751,0.00079857,0.0002491799,0.00001090743,0.00004960654,0.002518363],"genre_scores_gemma":[0.4683003,0.0007500779,0.5285628,0.001428528,0.0001661679,0.0001282144,0.0002932211,0.00009251949,0.0002782153],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1827095,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0237785230639043,"score_gpt":0.3925548408378162,"score_spread":0.3687763177739118,"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."}}