{"id":"W2963414887","doi":"10.1016/j.cels.2019.06.006","title":"Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data","year":2019,"lang":"en","type":"article","venue":"Cell Systems","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":199,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"National Institute of Environmental Health Sciences; National Cancer Institute","keywords":"Computational biology; Computer science; Biology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03570753,0.0006656842,0.001093549,0.003558601,0.001175861,0.004386535,0.00256563,0.001194773,0.003168644],"category_scores_gemma":[0.0975825,0.0006855024,0.001923966,0.007828145,0.001442048,0.00191457,0.003750459,0.00152023,0.001287611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002232702,"about_ca_system_score_gemma":0.003464202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01669658,"about_ca_topic_score_gemma":0.0198672,"domain_scores_codex":[0.9649428,0.01467396,0.00281795,0.008788006,0.007197383,0.001579865],"domain_scores_gemma":[0.9099797,0.03374752,0.005662275,0.03736601,0.01216788,0.001076626],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008882102,0.0006196612,0.4793567,0.003472771,0.00838472,0.001316587,0.008157265,0.0352846,0.04503103,0.01198629,0.07447217,0.3230361],"study_design_scores_gemma":[0.0005541446,0.001161183,0.7051908,0.0008242482,0.002446464,0.00123456,0.003445032,0.01641828,0.0420536,0.007239842,0.2190234,0.00040859],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7478464,0.002862866,0.07524293,0.002321361,0.0009480138,0.001495504,0.1504638,0.005929705,0.01288953],"genre_scores_gemma":[0.7443269,0.0004912943,0.06968777,0.0017444,0.0001517627,0.001328466,0.1765571,0.00347851,0.002233845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9642925,"threshold_uncertainty_score":0.1888418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620257314073815,"score_gpt":0.2697130753048708,"score_spread":0.2435105021641327,"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."}}