{"id":"W2146645587","doi":"10.1186/1756-9966-29-120","title":"An algorithm to discover gene signatures with predictive potential","year":2010,"lang":"en","type":"article","venue":"Journal of Experimental & Clinical Cancer Research","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McMaster University Medical Centre","funders":"Stem Cell Network","keywords":"Breast cancer; Gene expression profiling; Gene; Gene expression; Gene signature; Computational biology; Algorithm; Machine learning; Computer science; Bioinformatics; Cancer; Oncology; Medicine; Biology; Internal medicine; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001836079,0.001563158,0.00136979,0.003607555,0.0008895365,0.001743818,0.001939106,0.002074659,0.003937292],"category_scores_gemma":[0.008213146,0.0005393259,0.001279047,0.002765254,0.0008196341,0.001303086,0.001214906,0.001409723,0.001811581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008781525,"about_ca_system_score_gemma":0.001877879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002030093,"about_ca_topic_score_gemma":0.001494639,"domain_scores_codex":[0.9986855,0.0002567561,0.0001287125,0.0003807743,0.0004300643,0.0001182476],"domain_scores_gemma":[0.9966724,0.002094614,0.0001944479,0.0002102643,0.0007466129,0.00008153878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000481184,0.0003111117,0.006612969,0.0003038114,0.0002260038,0.0003570616,0.0001644872,0.1556357,0.007893764,0.009815034,0.011673,0.8065259],"study_design_scores_gemma":[0.0001433116,0.0001333917,0.0006539301,0.00003950872,0.00007399674,0.0003338884,0.00003503258,0.971828,0.004052791,0.018092,0.004593086,0.00002099433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01649866,0.0003073181,0.9769638,0.0004743585,0.00008436849,0.0003354403,0.000651474,0.003130381,0.001554128],"genre_scores_gemma":[0.08667528,0.0001513344,0.9087669,0.0002642152,0.00007708484,0.0007918992,0.001744117,0.0001401982,0.001388923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003937292,"threshold_uncertainty_score":0.01317161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03842146312314467,"score_gpt":0.4800361137865739,"score_spread":0.4416146506634293,"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."}}