{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005053371,0.0002080233,0.000204979,0.00003528282,0.0001346204,0.000008210607,0.0001040781,0.0001880097,0.00003136442],"category_scores_gemma":[0.00001467092,0.0001704133,0.00009669401,0.00004982584,0.0001810219,0.000001219172,0.00009420409,0.00004315959,0.000009488557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000490118,"about_ca_system_score_gemma":0.00008206157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000177548,"about_ca_topic_score_gemma":0.00009312844,"domain_scores_codex":[0.9988718,0.00004975087,0.0001797404,0.000480975,0.00004066093,0.0003770751],"domain_scores_gemma":[0.9994712,0.00003581495,0.00009204868,0.0002046647,0.0001482962,0.00004801576],"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":[0.0004263959,0.00009536315,0.05141178,0.00001071342,0.0001362437,0.00000346161,0.00002118047,0.00001965204,0.9448667,0.000115314,0.001779662,0.001113558],"study_design_scores_gemma":[0.002962057,0.0004272413,0.706583,0.00002489883,0.0001585908,0.000222223,0.00005512937,0.000008777401,0.2550248,0.0007039307,0.03323634,0.0005930897],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852539,0.005962571,0.001765128,0.001544784,0.0004003295,0.000755793,0.003498869,0.00003427434,0.000784296],"genre_scores_gemma":[0.9950733,0.00009492905,0.00159266,0.0002807201,0.0009503704,0.000508389,0.001024818,0.0000286307,0.0004462248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6898419,"threshold_uncertainty_score":0.6949254,"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."}}