{"id":"W2775659660","doi":"10.1007/s11306-017-1290-z","title":"Metabolomic prediction of endometrial cancer","year":2017,"lang":"en","type":"article","venue":"Metabolomics","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Metabolomics; Endometrial cancer; Cancer; Molecular medicine; Computational biology; Biology; Medicine; Bioinformatics; Genetics; Cell cycle","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":[0.0004966576,0.000584573,0.000502347,0.001186874,0.000214363,0.0008355372,0.0001898821,0.0004782184,0.001034039],"category_scores_gemma":[0.00130408,0.000140921,0.0006401409,0.001130853,0.0001249711,0.0002213997,0.000391243,0.0004366949,0.000254152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003997396,"about_ca_system_score_gemma":0.000392813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003491528,"about_ca_topic_score_gemma":0.004421564,"domain_scores_codex":[0.9997528,0.00009426353,0.00001425438,0.00004998641,0.00005302056,0.00003563535],"domain_scores_gemma":[0.9997641,0.00008846426,0.00006043956,0.00001686944,0.00004477878,0.00002529444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006138537,0.0004144702,0.5877993,0.0008209801,0.002203854,0.0008544303,0.0001088174,0.00852707,0.1367845,0.0009600084,0.005578338,0.2498098],"study_design_scores_gemma":[0.0002185272,0.001377376,0.831729,0.0003400209,0.00207838,0.001862611,0.0003866618,0.05808964,0.07931705,0.005366367,0.01912309,0.0001112119],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932945,0.04053119,0.009618926,0.002608998,0.0002032987,0.0001245954,0.008828603,0.0002175105,0.004921685],"genre_scores_gemma":[0.9862902,0.005181561,0.004640475,0.0004823844,0.00009312944,0.00003328137,0.002420352,0.00001474725,0.0008438805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003491528,"threshold_uncertainty_score":0.006942391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0524707945777973,"score_gpt":0.3276323874063554,"score_spread":0.2751615928285581,"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."}}