{"id":"W2766750745","doi":"10.1093/bioinformatics/btx707","title":"NanoStringNormCNV: pre-processing of NanoString CNV data","year":2017,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research; Prostate Cancer Canada; Terry Fox Research Institute; Ontario Institute for Cancer Research; Movember Foundation","keywords":"Computer science; Normalization (sociology); Visualization; Software; Copy-number variation; Data mining; Data processing; Software package; R package; Database; Computational science; Operating system; Biology; Gene","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":[0.005850804,0.002042314,0.001531874,0.003627118,0.001079857,0.002123915,0.002860843,0.001115287,0.04788063],"category_scores_gemma":[0.01858155,0.001499586,0.001978654,0.002183472,0.0009051083,0.00157925,0.002990853,0.002116402,0.02146461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001574178,"about_ca_system_score_gemma":0.002794567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004521962,"about_ca_topic_score_gemma":0.008605192,"domain_scores_codex":[0.9970821,0.0004916276,0.0002848511,0.001079909,0.0008085669,0.0002529279],"domain_scores_gemma":[0.9947266,0.002679834,0.0004904412,0.001139845,0.0007484899,0.0002147959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002306002,0.0001595333,0.02846875,0.002501625,0.0009164166,0.001032883,0.001124152,0.01297065,0.0486157,0.01051704,0.6946777,0.1967096],"study_design_scores_gemma":[0.001120851,0.0004132714,0.04049004,0.000479066,0.0003747051,0.001948835,0.0003355521,0.1305349,0.2003256,0.03480649,0.5885023,0.000668448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.03244101,0.0008340346,0.3565457,0.0008720442,0.0006113041,0.001478706,0.2313712,0.3670751,0.008770925],"genre_scores_gemma":[0.09202236,0.0004622604,0.499658,0.00142196,0.0001758098,0.006451146,0.2657697,0.1224703,0.0115685],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04788063,"threshold_uncertainty_score":0.1601766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027205727068864,"score_gpt":0.2912801544147864,"score_spread":0.2610080971440977,"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."}}