{"id":"W4389914218","doi":"10.3390/cancers15245895","title":"Feasibility Study Utilizing NanoString’s Digital Spatial Profiling (DSP) Technology for Characterizing the Immune Microenvironment in Barrett’s Esophagus Formalin-Fixed Paraffin-Embedded Tissues","year":2023,"lang":"en","type":"article","venue":"Cancers","topic":"Esophageal Cancer Research and Treatment","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal General Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute; American Cancer Society","keywords":"Barrett's esophagus; Tumor microenvironment; Dysplasia; Esophagus; Cancer research; Immune system; Multiplex; Stroma; Medicine; Pathology; Biology; Adenocarcinoma; Immunology; Immunohistochemistry; Internal medicine; Cancer; Bioinformatics","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":[0.0003133322,0.0001895816,0.0001056266,0.0003322829,0.0001172072,0.0002304505,0.0001411314,0.0002485247,0.0004446723],"category_scores_gemma":[0.0002246767,0.0001400951,0.0001549128,0.0002047276,0.0001511344,0.0002833428,0.0002101644,0.0001372691,0.0001632588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001138102,"about_ca_system_score_gemma":0.0001151538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002671118,"about_ca_topic_score_gemma":0.0006098578,"domain_scores_codex":[0.9998848,0.00002594343,0.000005902225,0.00003153456,0.00003559484,0.00001601012],"domain_scores_gemma":[0.9998968,0.00003232562,0.00002060921,0.00001277598,0.00002539802,0.00001213311],"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":[0.00009880881,0.0000179541,0.003429977,0.0000252447,0.000004872412,0.00005025844,0.00002182416,0.0001414259,0.9932013,0.00005144347,0.00002444696,0.002932483],"study_design_scores_gemma":[0.00001506107,0.0009869536,0.05843998,0.000009494019,0.00004377131,0.0008974004,0.0002038132,0.00715177,0.9301112,0.00009788085,0.00202823,0.0000143614],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861566,0.0003674878,0.01244816,0.00007275568,0.000009361773,0.00004448797,0.0001864427,0.00003905727,0.0006755235],"genre_scores_gemma":[0.9651222,0.0005000695,0.03284417,0.00007087078,0.000009046406,0.00007147202,0.0004445658,0.00001265745,0.0009248032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004446723,"threshold_uncertainty_score":0.001657069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04136769929332458,"score_gpt":0.3356273861279714,"score_spread":0.2942596868346468,"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."}}