{"id":"W2104230701","doi":"10.3390/metabo3020373","title":"The Future of NMR Metabolomics in Cancer Therapy: Towards Personalizing Treatment and Developing Targeted Drugs?","year":2013,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Alberta Cancer Foundation","keywords":"Metabolomics; Precision medicine; Personalized medicine; Cancer; Medicine; Cancer therapy; Drug; Cancer treatment; Drug discovery; Drug development; Computational biology; Bioinformatics; Pharmacology; Biology; Internal medicine; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002120928,0.0002012612,0.0003252049,0.00006167605,0.0001216618,0.00003941628,0.0001353013,0.00007673902,0.00002105607],"category_scores_gemma":[0.00003220071,0.000121408,0.00008679167,0.0001712186,0.0001018484,0.000007604072,0.00008111777,0.00005699065,9.311044e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001859974,"about_ca_system_score_gemma":0.00008710115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004844223,"about_ca_topic_score_gemma":0.0001770879,"domain_scores_codex":[0.9990236,0.00008033797,0.0002503433,0.0002712148,0.00009044621,0.0002841092],"domain_scores_gemma":[0.9995221,0.00002264778,0.0001085706,0.000202002,0.0001029676,0.00004174856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007489244,0.00006895633,0.02161757,0.00002062828,0.0006075564,3.609909e-7,0.001082131,0.000005779735,0.7416717,0.007127157,0.0003874083,0.2273358],"study_design_scores_gemma":[0.0009852116,0.0001000147,0.09195566,0.000007619597,0.00004338609,0.000001690616,0.001906388,0.0000351339,0.408807,0.0008226749,0.4950788,0.000256395],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7027921,0.2955464,0.0000172144,0.001121601,0.0001356026,0.0002075334,0.00001577143,0.000004078438,0.000159647],"genre_scores_gemma":[0.7714476,0.2252677,0.002167708,0.0001841335,0.0002595226,0.0001691049,0.0000154538,0.00001848157,0.0004703486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4946914,"threshold_uncertainty_score":0.4950876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135785972686215,"score_gpt":0.2641433638910651,"score_spread":0.2505647666224436,"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."}}