{"id":"W4411579153","doi":"10.1016/j.tranon.2025.102445","title":"Leveraging liquid biopsy to uncover resistance mechanisms and guide personalized immunotherapy","year":2025,"lang":"en","type":"review","venue":"Translational Oncology","topic":"Immunotherapy and Immune Responses","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Atlantic Cancer Research Institute","funders":"Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"Immunotherapy; Liquid biopsy; Resistance (ecology); Computer science; Biopsy; Medicine; Computational biology; Pathology; Immunology; Biology; Internal medicine; Immune system; Cancer","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003911957,0.001028597,0.001470104,0.003684263,0.0007070155,0.004250744,0.001132106,0.002540989,0.006283164],"category_scores_gemma":[0.006038927,0.0008256355,0.001256486,0.001064071,0.001551193,0.004780301,0.001886301,0.003857994,0.004490906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009612161,"about_ca_system_score_gemma":0.001576263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001861445,"about_ca_topic_score_gemma":0.002717372,"domain_scores_codex":[0.99823,0.0006135229,0.000137624,0.0003320795,0.0005323357,0.0001544501],"domain_scores_gemma":[0.9965862,0.001207854,0.0005391466,0.0004446231,0.0008919157,0.000330229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001590256,0.0004479221,0.054656,0.003593463,0.0004940464,0.004801572,0.000759301,0.006256649,0.203058,0.01986439,0.05995535,0.644523],"study_design_scores_gemma":[0.0003574078,0.001544787,0.03305468,0.004483201,0.001220914,0.02158655,0.002975313,0.0658449,0.1886943,0.07980318,0.5999333,0.0005015333],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0969495,0.1971188,0.6184609,0.03267987,0.004891149,0.001363975,0.003223164,0.007420224,0.03789252],"genre_scores_gemma":[0.4977909,0.1140381,0.3335238,0.02729813,0.004333999,0.001145594,0.003653914,0.001944627,0.01627104],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006283164,"threshold_uncertainty_score":0.02101928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03081677929351977,"score_gpt":0.3389165680546153,"score_spread":0.3080997887610955,"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."}}