{"id":"W2945998739","doi":"10.1158/1078-0432.ccr-19-0585","title":"Comprehensive Genomic Profiling Identifies Novel Genetic Predictors of Response to Anti–PD-(L)1 Therapies in Non–Small Cell Lung Cancer","year":2019,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cancer Immunotherapy and Biomarkers","field":"Medicine","cited_by":236,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Science and Technology Planning Project of Guangdong Province; National Key Research and Development Program of China; Sun Yat-sen University; National Natural Science Foundation of China","keywords":"Lung cancer; Medicine; Oncology; Internal medicine; Immunotherapy; Cancer; Copy-number variation; Cancer research; Gene; Biology; Genetics; Genome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002722288,0.0002283228,0.0007761811,0.0004990139,0.00007278147,0.0000381609,0.0004353439,0.000239645,0.000594172],"category_scores_gemma":[0.0001864071,0.0001948922,0.0002439579,0.0009013387,0.0004208311,0.00006027821,0.0002398935,0.0008393432,0.00003398605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004465544,"about_ca_system_score_gemma":0.001493238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003489139,"about_ca_topic_score_gemma":0.0004859866,"domain_scores_codex":[0.9962916,0.000491383,0.00107572,0.0007254059,0.0007228604,0.0006930192],"domain_scores_gemma":[0.9969724,0.00129555,0.0001685343,0.00070063,0.0006322854,0.0002305717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01630234,0.0002109154,0.4861114,0.0005203045,0.0001654453,0.00001187738,0.0009629649,0.0001552269,0.492951,6.431029e-7,0.000437372,0.002170477],"study_design_scores_gemma":[0.005979656,0.0009808459,0.9459769,0.0008403871,0.00004160662,0.000002437795,0.0009574824,0.0003865274,0.04034039,0.000004927283,0.004284095,0.0002048111],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834629,0.01127208,0.00001802779,0.001324878,0.000933114,0.002752794,0.00008399104,0.00002258444,0.0001295739],"genre_scores_gemma":[0.9910864,0.005175134,0.0003609245,0.0004791575,0.0003324874,0.0003226272,0.000005965355,0.00006091335,0.002176365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4598655,"threshold_uncertainty_score":0.7947472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172463546394366,"score_gpt":0.4609627422534374,"score_spread":0.3437163876140008,"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."}}