{"id":"W2955886650","doi":"10.1158/1538-7445.am2019-lb-225","title":"Abstract LB-225: RNA molecular signatures as predictive biomarkers of response to monotherapy pembrolizumab in patients with metastatic triple-negative breast cancer: KEYNOTE-086","year":2019,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Pembrolizumab; Medicine; Oncology; Internal medicine; Triple-negative breast cancer; Breast cancer; Cohort; Tumor-infiltrating lymphocytes; Cancer; Gene signature; Gene expression; Immunotherapy; Gene; Biology","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":[0.0005092563,0.0002598196,0.0004459101,0.0003004888,0.0001948436,0.0006374521,0.0002669753,0.0003038632,0.001478538],"category_scores_gemma":[0.0007450961,0.0001463189,0.0001936202,0.0003006312,0.0001757784,0.0002280444,0.0002747154,0.0004524008,0.0004455706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000414498,"about_ca_system_score_gemma":0.0002478749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004793596,"about_ca_topic_score_gemma":0.0008791466,"domain_scores_codex":[0.9997777,0.0000533641,0.00001955994,0.00008081664,0.00004457223,0.00002391662],"domain_scores_gemma":[0.9995993,0.00007567429,0.0001505115,0.00003531944,0.00006545398,0.00007385012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03348677,0.001070239,0.7823169,0.0004024954,0.0005378428,0.0002573159,0.000162967,0.001910181,0.114882,0.0001444298,0.003414901,0.06141404],"study_design_scores_gemma":[0.001240663,0.0082293,0.9565834,0.00005454367,0.000500294,0.001264732,0.0001868697,0.007146141,0.02030614,0.0002060824,0.004244719,0.000037105],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997262,0.0004829369,0.0002151536,0.00006550421,0.00001042188,0.00003827289,0.001311032,0.00002139089,0.0005931896],"genre_scores_gemma":[0.9958747,0.0001196725,0.0006287407,0.0001035708,0.00002310163,0.00006003403,0.002606917,0.000005502939,0.0005777815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001478538,"threshold_uncertainty_score":0.004946232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742878176680748,"score_gpt":0.3501565428494182,"score_spread":0.3327277610826107,"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."}}