{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001063828,0.0001693958,0.0002046989,0.0001843718,0.0001312137,0.00009738754,0.0004250142,0.0002547319,0.00005928116],"category_scores_gemma":[0.0003472184,0.0001472757,0.00008501382,0.0001865416,0.0004803375,0.00001535595,0.0002950931,0.0005249373,0.00000417045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000643319,"about_ca_system_score_gemma":0.0009719639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00085344,"about_ca_topic_score_gemma":0.0003085772,"domain_scores_codex":[0.9982033,0.00008513633,0.0002591265,0.0005544955,0.0002853804,0.0006125642],"domain_scores_gemma":[0.9986662,0.00006223162,0.0000734945,0.0004888824,0.0005452509,0.0001639145],"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":[0.0007232754,0.00004726277,0.03334006,0.0002170862,0.0000692813,0.000003161474,0.00003461709,8.111888e-7,0.9617235,0.00005589454,0.0006663771,0.003118697],"study_design_scores_gemma":[0.0007722071,0.0001663773,0.05708118,0.00002361499,0.000005931783,0.000004990765,0.00006642872,0.0000426053,0.9371008,0.0000690728,0.004513372,0.0001534154],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968021,0.000651389,0.0001488964,0.0002504889,0.0001506772,0.001417182,0.0003882289,0.000006537406,0.0001845238],"genre_scores_gemma":[0.9973758,0.0001586782,0.001059914,0.00001284746,0.000226038,0.0004079824,0.0001485776,0.00005292432,0.0005572116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02462268,"threshold_uncertainty_score":0.6005731,"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."}}