{"id":"W2886206553","doi":"10.1007/s11306-018-1398-9","title":"Metabolomic identification of diagnostic serum-based biomarkers for advanced stage melanoma","year":2018,"lang":"en","type":"article","venue":"Metabolomics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Metabolomics; Identification (biology); Computational biology; Melanoma; Diagnostic biomarker; Molecular medicine; Biology; Medicine; Biomarker; Cancer research; Bioinformatics; Cancer; 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":[0.0004202662,0.000398564,0.0003587096,0.001169546,0.0001935639,0.000635723,0.0001586075,0.0004435589,0.0005388257],"category_scores_gemma":[0.0008960241,0.0001386067,0.0002071135,0.0006421161,0.0001450649,0.0002312821,0.0002293284,0.0003789739,0.0001505074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002668012,"about_ca_system_score_gemma":0.0002830566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007460692,"about_ca_topic_score_gemma":0.001022294,"domain_scores_codex":[0.9997892,0.00006235766,0.00001861275,0.00003611822,0.00006247135,0.00003130909],"domain_scores_gemma":[0.999798,0.00004885207,0.0000579321,0.0000107133,0.00005567229,0.00002888009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003502098,0.0003062191,0.265588,0.0002791982,0.0002387562,0.0005599933,0.0001481938,0.0005297765,0.6679747,0.0004288325,0.0008361588,0.05960818],"study_design_scores_gemma":[0.0001029002,0.001615974,0.4310438,0.00008832072,0.0004507199,0.002814339,0.0004188877,0.009241278,0.5482124,0.001213946,0.004756148,0.00004129234],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839845,0.007736777,0.00537289,0.0004517507,0.00007025027,0.00005192052,0.001017871,0.00009281936,0.001221166],"genre_scores_gemma":[0.9949061,0.0009423053,0.00308985,0.0001510401,0.00002871081,0.0000218296,0.0004072166,0.000006260187,0.0004467382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001169546,"threshold_uncertainty_score":0.002222657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110258247678577,"score_gpt":0.2680254145504491,"score_spread":0.2569995897825914,"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."}}