{"id":"W3112394590","doi":"10.1002/mco2.46","title":"Pathway‐extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors","year":2020,"lang":"en","type":"article","venue":"MedComm","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cytodiagnostics (Canada); London Health Sciences Centre; Western University","funders":"Compute Canada","keywords":"Erlotinib; Lapatinib; Sunitinib; Gefitinib; Sorafenib; Pharmacogenomics; Tyrosine kinase; Tyrosine-kinase inhibitor; Cancer; Precision medicine; Drug; Personalized medicine; Medicine; Computational biology; Pharmacology; Bioinformatics; Biology; Cancer research; Epidermal growth factor receptor; Internal medicine; Breast cancer; Receptor; Hepatocellular carcinoma","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":[],"consensus_categories":[],"category_scores_codex":[0.00006327614,0.0001756033,0.0002520225,0.0001331874,0.00009051293,0.00001293984,0.00007944568,0.00008234726,0.00005998803],"category_scores_gemma":[0.0002249147,0.0001257256,0.0001162237,0.000279714,0.00005374882,0.00007241307,0.00007371033,0.0001417396,0.000007986257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000111171,"about_ca_system_score_gemma":0.0002053142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001002448,"about_ca_topic_score_gemma":0.00001007357,"domain_scores_codex":[0.9988953,0.00004714859,0.0002750323,0.0002985169,0.0002962039,0.0001877608],"domain_scores_gemma":[0.9991085,0.0000682747,0.0001138244,0.0002758484,0.0001182726,0.0003152676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001303901,0.0004802841,0.002216781,0.00006223916,0.0002164084,0.00003584374,0.004218131,0.00004846037,0.9725474,0.00003332501,0.006126004,0.01271123],"study_design_scores_gemma":[0.001901675,0.001542986,0.008617595,0.0002435755,0.0001888657,0.000005540746,0.00179758,0.0001906005,0.9741647,0.00001896056,0.0111837,0.0001441952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986315,0.0007554262,0.002416824,0.007264589,0.0005542631,0.001153385,0.000630594,0.0001350167,0.0007748732],"genre_scores_gemma":[0.9933619,0.00001935324,0.004977807,0.001120799,0.0001000374,0.0001354651,0.0001017629,0.00002700431,0.0001558075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01256703,"threshold_uncertainty_score":0.5126942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837106154799912,"score_gpt":0.2870220119581514,"score_spread":0.2686509504101522,"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."}}