{"id":"W2050167587","doi":"10.1016/j.gdata.2013.09.001","title":"Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients","year":2013,"lang":"en","type":"article","venue":"Genomics Data","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Anthracycline; Breast cancer; Epirubicin; Oncology; Gene expression profiling; Internal medicine; Estrogen receptor; Topoisomerase; Predictive value; Bioinformatics; Medicine; Biology; Gene expression; Gene; Cancer; Computational biology; DNA; Genetics","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":[0.0001349757,0.0001657507,0.000141027,0.00008912335,0.00007117915,0.0000517544,0.0007926429,0.0000995937,0.00004602009],"category_scores_gemma":[0.00007435566,0.0001585849,0.00002241253,0.0001678835,0.00001932668,0.00001970321,0.0007493566,0.00007147664,0.00005676768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006616134,"about_ca_system_score_gemma":0.0001086185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004862935,"about_ca_topic_score_gemma":0.0001178911,"domain_scores_codex":[0.9984418,0.00004180453,0.0003211101,0.0007515194,0.0001466293,0.0002971845],"domain_scores_gemma":[0.9983643,0.000006801809,0.00009356387,0.001211463,0.0001324296,0.0001914354],"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":[0.0001075941,0.0000751652,0.06776847,0.00001394822,0.000006653226,2.838361e-7,0.0000448575,0.0002305886,0.9110827,8.223398e-7,0.01954253,0.001126335],"study_design_scores_gemma":[0.0005978319,0.00004859777,0.4501435,0.00006385966,0.000006934526,6.736241e-7,0.00008218461,0.00008010428,0.4515041,0.00001966066,0.09711214,0.0003404547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942504,0.000345581,0.001763052,0.001287057,0.0002331628,0.0007549405,0.001230267,0.00001247616,0.0001230245],"genre_scores_gemma":[0.9864716,0.0005186048,0.008291199,0.0009315171,0.0003386655,0.0003109835,0.002581923,0.0000396597,0.0005158394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4595787,"threshold_uncertainty_score":0.6466905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764317370359748,"score_gpt":0.2697781778408685,"score_spread":0.252135004137271,"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."}}