{"id":"W2088766251","doi":"10.1158/1538-7445.am10-3037","title":"Abstract 3037: Integrated Genomic, MicroRNA (miRNA) and Proteomic Profiling of Ovarian Carcinoma for Biomarker Discovery","year":2010,"lang":"en","type":"article","venue":"Cancer Research","topic":"Kruppel-like factors research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Hospital for Sick Children; SickKids Foundation; Toronto General Hospital; University Health Network; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"microRNA; Biomarker; Biology; Ovarian cancer; Locus (genetics); Genome instability; Malignancy; Gene expression profiling; Cancer research; Oncology; Bioinformatics; Computational biology; DNA damage; Gene expression; Cancer; Gene; Genetics; Medicine; DNA","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":[0.0004809187,0.0002704748,0.0003501182,0.0008318237,0.0002179279,0.0004475952,0.0001784842,0.0004045474,0.002635223],"category_scores_gemma":[0.0004937619,0.0001723726,0.0002685002,0.0005130632,0.0001460782,0.0002784798,0.0003367221,0.0003041339,0.001079733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002165862,"about_ca_system_score_gemma":0.0002679144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003162077,"about_ca_topic_score_gemma":0.0004975406,"domain_scores_codex":[0.999795,0.00003014528,0.00002196723,0.0000441534,0.00008371031,0.00002504885],"domain_scores_gemma":[0.9998295,0.00003727221,0.0000337355,0.0000140433,0.00005288847,0.00003244804],"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":[0.0002250025,0.00002715556,0.007620594,0.0001028171,0.00002616768,0.0001559057,0.0000213718,0.00009963043,0.9856301,0.00006568071,0.0002289937,0.005796608],"study_design_scores_gemma":[0.00005905656,0.0007835682,0.2156656,0.00003717273,0.0001451227,0.003527168,0.0001846936,0.008812327,0.7578192,0.0003706913,0.01256033,0.00003501068],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757947,0.003613828,0.01317353,0.0002964602,0.0000915692,0.0001906032,0.003795684,0.0002268531,0.002816777],"genre_scores_gemma":[0.9668,0.001148672,0.02385382,0.0002023949,0.00003075871,0.0002020853,0.00374326,0.00006349334,0.003955543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002635223,"threshold_uncertainty_score":0.008815646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819289675544176,"score_gpt":0.3713560918448908,"score_spread":0.323163195089449,"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."}}