{"id":"W2937662637","doi":"10.3390/metabo9040072","title":"CFM-ID 3.0: Significantly Improved ESI-MS/MS Prediction and Compound Identification","year":2019,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":264,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Genome Alberta; Genome Canada","keywords":"Identification (biology); Computer science; Metadata; Mass spectrometry; Tandem mass spectrometry; Pattern recognition (psychology); Chemistry; Artificial intelligence; Chromatography; Biology","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":[0.0003200725,0.0001838632,0.0002539685,0.00008187192,0.0001037017,0.00007563859,0.0001302095,0.0001035221,0.00005733305],"category_scores_gemma":[0.00009921935,0.0001652665,0.0000686535,0.000122249,0.00007359477,0.00001126864,0.00010654,0.00007965926,0.00003039767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007617186,"about_ca_system_score_gemma":0.00002468734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003971678,"about_ca_topic_score_gemma":0.00001387363,"domain_scores_codex":[0.9988126,0.00005793113,0.0002845799,0.0004759588,0.0001231638,0.0002458344],"domain_scores_gemma":[0.9992645,0.00001975763,0.0001723261,0.0003777464,0.00009537793,0.00007028576],"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":[0.00003757407,0.00004059362,0.01846043,0.00002534771,0.0001091089,2.422547e-7,0.000034,0.00000247168,0.9786053,0.001256033,0.000500309,0.0009286354],"study_design_scores_gemma":[0.0008365986,0.0001866973,0.2012886,0.000005216151,0.0001088405,0.000009499591,0.0001394588,0.0003059309,0.6253876,0.0005150599,0.1709263,0.0002901845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892805,0.007357287,0.0006208155,0.0001270376,0.0004980558,0.0003508837,0.0001105847,0.00002661438,0.001628231],"genre_scores_gemma":[0.9944131,0.001873259,0.0007812808,0.000101962,0.0002890597,0.00003374412,0.0002561759,0.00002263837,0.002228829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3532177,"threshold_uncertainty_score":0.673937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006506425331549946,"score_gpt":0.2214065229568456,"score_spread":0.2149000976252956,"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."}}