{"id":"W2956419562","doi":"10.3390/metabo9070144","title":"MolNetEnhancer: Enhanced Molecular Networks by Integrating Metabolome Mining and Annotation Tools","year":2019,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":382,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Netherlands eScience Center; University of California, San Diego; University of Alberta; National Science Foundation","keywords":"Annotation; Workflow; Computer science; Metabolome; In silico; Metabolomics; Computational biology; Chemical space; Visualization; Data mining; Data science; Bioinformatics; Drug discovery; Biology; Artificial intelligence; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002636157,0.001521724,0.0007471062,0.003311477,0.0009310524,0.00222815,0.001934104,0.0008559949,0.009567114],"category_scores_gemma":[0.004200045,0.0009275122,0.001307042,0.001896659,0.0005407687,0.003036953,0.002332965,0.001453817,0.002683824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215609,"about_ca_system_score_gemma":0.001262952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003035074,"about_ca_topic_score_gemma":0.007140611,"domain_scores_codex":[0.999388,0.0001478691,0.000051602,0.000186512,0.0001811277,0.00004496859],"domain_scores_gemma":[0.9984657,0.0008395896,0.0001642338,0.0002678073,0.0001556794,0.000107059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003164385,0.0006342038,0.01941845,0.003852717,0.0008728673,0.001850924,0.001921159,0.1068496,0.1465633,0.0657618,0.1166286,0.532482],"study_design_scores_gemma":[0.000215561,0.0002114426,0.00437774,0.0002748617,0.0001758262,0.0005378451,0.0002408934,0.6628577,0.0777691,0.05929348,0.1938519,0.0001938317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0277508,0.0007088488,0.7757912,0.0008603935,0.0002434842,0.0003019266,0.01501818,0.1733901,0.005935034],"genre_scores_gemma":[0.1059597,0.000974426,0.8488165,0.0003449841,0.00007221364,0.0006015319,0.02887209,0.009749261,0.004609234],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.009567114,"threshold_uncertainty_score":0.03200519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005017852499028722,"score_gpt":0.2268309248008978,"score_spread":0.2218130723018691,"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."}}