{"id":"W4389839591","doi":"10.1016/j.jtocrr.2023.100623","title":"Brief Report: Comprehensive Clinicogenomic Profiling of Small Cell Transformation From EGFR-Mutant NSCLC Informs Potential Therapeutic Targets","year":2023,"lang":"en","type":"article","venue":"JTO Clinical and Research Reports","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Genentech; National Institutes of Health; Mirati Therapeutics; Regeneron Pharmaceuticals; Daiichi Sankyo Europe; Sanofi; GlaxoSmithKline; Eli Lilly and Company; AstraZeneca; Damon Runyon Cancer Research Foundation; LUNGevity Foundation; Computer Modelling Group; Amgen; Cancer Prevention and Research Institute of Texas; University of Texas MD Anderson Cancer Center; V Foundation for Cancer Research","keywords":"Profiling (computer programming); Mutant; Transformation (genetics); Cancer research; Oncology; Computational biology; Medicine; Biology; Computer science; Gene; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006623702,0.0002246355,0.0008926088,0.0003237271,0.0002704303,0.00005321407,0.0001432895,0.0002828034,0.00006298594],"category_scores_gemma":[0.001966058,0.0001560773,0.0003490675,0.0005948001,0.0009856006,0.0001451325,0.0003316991,0.001217397,0.00003361524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009342936,"about_ca_system_score_gemma":0.001038724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005057165,"about_ca_topic_score_gemma":0.00003456874,"domain_scores_codex":[0.9940618,0.0003223087,0.002370684,0.0007163702,0.001768861,0.0007600188],"domain_scores_gemma":[0.9956744,0.001197275,0.0004655494,0.0007058134,0.001502558,0.0004544023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008994841,0.00228071,0.5059611,0.004974218,0.003070487,0.04556911,0.005856164,0.0001357013,0.198232,0.0001814086,0.007191608,0.2175527],"study_design_scores_gemma":[0.01005399,0.004987623,0.8477963,0.001094544,0.0005030733,0.00156705,0.005694591,0.00440617,0.06526286,0.01016524,0.04761342,0.0008550893],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903972,0.002410494,0.000145153,0.002093974,0.0005004226,0.001887195,0.00003613884,0.0001107833,0.002418686],"genre_scores_gemma":[0.9928075,0.005084452,0.0004076535,0.0001367603,0.0004787598,0.00008768442,0.00022297,0.00003754602,0.0007366739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3418353,"threshold_uncertainty_score":0.6364646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1404393992648889,"score_gpt":0.4482286477040534,"score_spread":0.3077892484391644,"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."}}