{"id":"W4362542218","doi":"10.1158/1538-7445.am2023-939","title":"Abstract 939: Genomic characterization of PMBCL, cHL and DLBCL utilizing tissue and liquid biopsies","year":2023,"lang":"en","type":"article","venue":"Cancer Research","topic":"Lymphoma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Lymphoma; Cancer research; Liquid biopsy; Cancer; Gene; Pathology; Population; Medicine; Biology; Internal medicine; Genetics","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":[0.0002821613,0.0001928912,0.0001759191,0.001079865,0.0002331919,0.0003406813,0.0001809789,0.0002076242,0.002245108],"category_scores_gemma":[0.0004780673,0.0001011907,0.0001532061,0.0004635416,0.0002347752,0.0001461117,0.0002892331,0.0001872714,0.0004183066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002999916,"about_ca_system_score_gemma":0.000196091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002333117,"about_ca_topic_score_gemma":0.001802357,"domain_scores_codex":[0.9997832,0.00002935186,0.00002608224,0.00006777023,0.00005780046,0.00003578717],"domain_scores_gemma":[0.9998339,0.00003710087,0.00003789378,0.00002068005,0.00003885491,0.00003149821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007905237,0.00004736276,0.754843,0.00007472927,0.00005633061,0.002020798,0.0003396357,0.0001532443,0.2257641,0.00008130536,0.0001655232,0.01566355],"study_design_scores_gemma":[0.00002662161,0.000360903,0.957214,0.00001313877,0.00006633349,0.008231609,0.000420841,0.001164136,0.03111462,0.00007283654,0.001308719,0.000006272005],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983613,0.0001616,0.0006246414,0.00001554794,0.000002112837,0.00002156913,0.0003028107,0.00001387858,0.0004964914],"genre_scores_gemma":[0.9985415,0.00005177627,0.0005842013,0.00002268609,0.00000429155,0.00002034282,0.000550151,0.000004565048,0.0002204078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002333117,"threshold_uncertainty_score":0.007510602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064732724204629,"score_gpt":0.4201807178689819,"score_spread":0.313707445448519,"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."}}