{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007352451,0.0006857681,0.00223036,0.0006112634,0.0003933088,0.00003148628,0.0005081756,0.001093768,0.001420171],"category_scores_gemma":[0.0000834599,0.0006097436,0.0005694124,0.0004660726,0.0003082358,0.00009767788,0.0000671678,0.0006831333,0.0003023757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002452237,"about_ca_system_score_gemma":0.001702606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002934073,"about_ca_topic_score_gemma":0.00001409845,"domain_scores_codex":[0.9962279,0.001207515,0.001111364,0.0007754982,0.00009330382,0.0005844097],"domain_scores_gemma":[0.9972093,0.001854027,0.0003270761,0.000449914,0.0001212157,0.00003854129],"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":[0.005330455,0.0002665091,5.336743e-7,0.003135549,0.002441935,0.00003673706,0.001241761,0.000002569924,0.008487168,0.02170168,0.004573588,0.9527815],"study_design_scores_gemma":[0.001942868,0.0004395137,0.0000060853,0.003420272,0.0003676739,0.0001940731,0.00004570054,1.092667e-7,0.0001337594,0.0004646135,0.9924155,0.000569817],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002311665,0.9859754,0.006546285,0.0008423834,0.0009807146,0.001164664,0.0002097232,0.0001046611,0.004153066],"genre_scores_gemma":[0.00001490595,0.9349014,0.002972329,0.0008512394,0.0000461458,0.0002939778,0.0004499383,0.00006857589,0.06040147],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9878419,"threshold_uncertainty_score":0.9996354,"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."}}