{"id":"W4393567734","doi":"10.5281/zenodo.6323593","title":"Xena TCGA TARGET TCGx RNAseq Data","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"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":[],"consensus_categories":[],"category_scores_codex":[0.001349585,0.002171732,0.001963733,0.002267694,0.001140359,0.002314275,0.003292087,0.002165356,0.05565173],"category_scores_gemma":[0.003169002,0.0008255851,0.001370305,0.004292355,0.0005259574,0.0007141856,0.001875725,0.002191136,0.06611627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322135,"about_ca_system_score_gemma":0.00218251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01163836,"about_ca_topic_score_gemma":0.02275935,"domain_scores_codex":[0.9989249,0.000190062,0.00008190142,0.0004023399,0.0002376668,0.0001630494],"domain_scores_gemma":[0.9987981,0.0003345913,0.00009261876,0.0004098333,0.0002192488,0.0001455784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004382056,0.00006543259,0.001942172,0.001412899,0.0001566204,0.0001031342,0.00005480169,0.001347584,0.003079757,0.00114171,0.9854838,0.00477382],"study_design_scores_gemma":[0.0006985314,0.00008942693,0.007566674,0.0002576143,0.0001708465,0.000265517,0.00007763399,0.001517683,0.004969812,0.002889384,0.981427,0.00006976809],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005525366,0.0001109478,0.0002786698,0.0000429965,0.00002190319,0.00001936578,0.9975398,0.000766695,0.0006672005],"genre_scores_gemma":[0.000647127,0.00004152113,0.0004186782,0.00004617981,0.000003666067,0.0001124381,0.9981046,0.0001689689,0.0004568437],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05565173,"threshold_uncertainty_score":0.1861736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03667822658597382,"score_gpt":0.2773289074274556,"score_spread":0.2406506808414818,"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."}}