{"id":"W2113957930","doi":"10.1186/gb-2006-7-10-r101","title":"A consensus prognostic gene expression classifier for ER positive breast cancer","year":2006,"lang":"en","type":"article","venue":"Genome biology","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre","funders":"Fundação para a Ciência e a Tecnologia; Isaac Newton Trust; Cancer Research UK","keywords":"Classifier (UML); Breast cancer; Estrogen receptor; Oncology; Microarray; Internal medicine; Medicine; Biology; Gene; Gene expression; Artificial intelligence; Cancer; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005672707,0.0005231944,0.00116738,0.002135324,0.0004677322,0.001236811,0.0007594556,0.00112905,0.001735127],"category_scores_gemma":[0.0133326,0.0001343645,0.0004652066,0.00127408,0.00048474,0.001028039,0.0007562703,0.0009652371,0.001275459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000752151,"about_ca_system_score_gemma":0.000951193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004525105,"about_ca_topic_score_gemma":0.0005700524,"domain_scores_codex":[0.9978739,0.0004228293,0.0002215779,0.0004984589,0.0007315103,0.000251731],"domain_scores_gemma":[0.9941899,0.002333338,0.0008830826,0.0005982123,0.001707605,0.0002879651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003066593,0.0007056399,0.4948586,0.0005004161,0.0005149558,0.0003527801,0.0001887394,0.03202777,0.06255759,0.002723315,0.01083502,0.3916686],"study_design_scores_gemma":[0.0004340343,0.002054391,0.2962502,0.0002061789,0.001062071,0.002400123,0.0004508368,0.5624474,0.101255,0.0224252,0.01082314,0.0001915008],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.792133,0.002094973,0.1949665,0.001384907,0.0001810314,0.0002602279,0.003485687,0.001168119,0.004325649],"genre_scores_gemma":[0.9391268,0.0001901007,0.0565126,0.0002155247,0.00009409698,0.0001727275,0.003175003,0.00006094659,0.0004521484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005672707,"threshold_uncertainty_score":0.03000051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042477222011619,"score_gpt":0.2597880905257928,"score_spread":0.2493633183056766,"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."}}