{"id":"W2624569919","doi":"10.1158/1557-3265.ovcasymp16-dpoc-014","title":"Abstract DPOC-014: BEYOND CODING MUTATIONS: USING RETROTRANSPOSONS TO PREDICT OVARIAN CANCER DEVELOPMENT","year":2017,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"","keywords":"Ovarian cancer; Sanger sequencing; Endometriosis; Biology; Cancer research; Frameshift mutation; Cancer; Epigenetics; Retrotransposon; Massive parallel sequencing; Genetics; Mutation; Medicine; DNA sequencing; Gene; Genome; Pathology","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":[0.0003753597,0.0002474463,0.0001718582,0.001199282,0.0001664606,0.0004246056,0.0002492076,0.0004404927,0.001579502],"category_scores_gemma":[0.001200024,0.0001126207,0.0001460955,0.0004875018,0.0002647909,0.0001610093,0.0002712555,0.0003019411,0.0002671413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001776504,"about_ca_system_score_gemma":0.0001154595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001106907,"about_ca_topic_score_gemma":0.0009846522,"domain_scores_codex":[0.9997726,0.00005237007,0.00002303981,0.00005693794,0.00006123469,0.0000337937],"domain_scores_gemma":[0.9993376,0.0002111755,0.0001958615,0.00003386482,0.0001005783,0.0001209852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003595792,0.00002550325,0.980667,0.00002556476,0.00002183402,0.0002988924,0.00002937798,0.0001008959,0.01358359,0.00002049994,0.00008779614,0.004779507],"study_design_scores_gemma":[0.0000278137,0.0003454199,0.9811968,0.00001527824,0.00006582432,0.003771172,0.0001757378,0.00231336,0.01092459,0.00009542881,0.001062686,0.000005966843],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982879,0.0003517228,0.0004218664,0.00003020393,0.000006436421,0.00002314657,0.0002609147,0.00001483576,0.0006031243],"genre_scores_gemma":[0.9986808,0.00007656894,0.0006549298,0.00001885972,0.000004793977,0.0000102781,0.0003057983,0.000003490971,0.000244543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001579502,"threshold_uncertainty_score":0.005283952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2348676825987793,"score_gpt":0.5157947380122851,"score_spread":0.2809270554135058,"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."}}