{"id":"W2906067026","doi":"10.1021/acs.jproteome.8b00720","title":"CEU Mass Mediator 3.0: A Metabolite Annotation Tool","year":2018,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":164,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Ministerio de Economía y Competitividad; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"Metadata; Computer science; Annotation; Ontology; Knowledge base; Database; Identification (biology); Information retrieval; Metabolome; Service (business); Metabolomics; World Wide Web; Bioinformatics; Biology; Artificial intelligence","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":[0.003790655,0.00009665309,0.0002138718,0.0003412731,0.0002098849,0.00006598954,0.000301895,0.0001065043,0.00006695656],"category_scores_gemma":[0.001906162,0.00007719264,0.0001108452,0.0003586351,0.0002473539,0.00001233012,0.0001131644,0.0002981801,0.00002550676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003595158,"about_ca_system_score_gemma":0.0003506749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007522543,"about_ca_topic_score_gemma":0.000006704746,"domain_scores_codex":[0.9980737,0.0003153483,0.0003553332,0.0001753874,0.0006834453,0.0003967653],"domain_scores_gemma":[0.9976183,0.00003702661,0.0001790722,0.0002274244,0.001806641,0.0001314983],"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":[0.000235117,0.0000472598,0.001615608,0.0000207725,0.0001338058,0.000009734727,0.0001014219,4.828387e-7,0.990485,0.0009115596,0.004456239,0.001982971],"study_design_scores_gemma":[0.0008038555,0.00128779,0.005282169,0.00001929308,0.00002120764,0.00002828162,0.0002452847,0.00001085253,0.6519851,0.002204547,0.3379733,0.0001382877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877501,0.003588614,0.003870912,0.00174557,0.0003821745,0.0003805024,0.00001250226,0.000003655056,0.002265928],"genre_scores_gemma":[0.9759381,0.002695363,0.01602839,0.00006755629,0.003682458,0.00002509225,0.000005202064,0.0000220095,0.001535767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3384999,"threshold_uncertainty_score":0.3147825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548476138424697,"score_gpt":0.3856850958765461,"score_spread":0.3402003344922992,"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."}}