{"id":"W2126757300","doi":"10.1093/bioinformatics/bts662","title":"Visualization and Phospholipid Identification (VaLID): online integrated search engine capable of identifying and visualizing glycerophospholipids with given mass","year":2012,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Institutes of Health Research; University of Ottawa","keywords":"Lipidomics; Glycerophospholipids; Visualization; Identification (biology); Computer science; Glycerophospholipid; Computational biology; Degree of unsaturation; Phospholipid; Data visualization; Bioinformatics; Data science; Information retrieval; Chemistry; Data mining; Biology; Biochemistry; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003487322,0.0001512057,0.0002094896,0.0001051299,0.00009421098,0.0000357069,0.00007545363,0.0000864414,0.000005886649],"category_scores_gemma":[0.00006378649,0.0001292434,0.00002525033,0.00021792,0.0001060636,0.00003816672,0.00009644957,0.00006530869,0.000001305937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001530984,"about_ca_system_score_gemma":0.00002687447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004028743,"about_ca_topic_score_gemma":0.000007935358,"domain_scores_codex":[0.9990731,0.00002601615,0.0003586874,0.000133536,0.0001649804,0.0002436225],"domain_scores_gemma":[0.9993896,0.00001323962,0.0001794625,0.0001824316,0.0001500819,0.00008516024],"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":[0.0002735522,0.0002209893,0.04116768,0.001087104,0.0004303506,5.417722e-7,0.003804177,0.00005531136,0.9352788,0.003147276,0.0004981136,0.01403613],"study_design_scores_gemma":[0.001436691,0.0004493568,0.0237662,0.0001024111,0.0001490206,0.00003115191,0.005965254,0.01001867,0.9489769,0.00003892254,0.00860029,0.0004650728],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9578536,0.002967885,0.03868975,0.00001951756,0.0001110825,0.0001939454,0.00005431187,0.00001307362,0.00009688987],"genre_scores_gemma":[0.9802855,0.00343043,0.01576889,0.00003546024,0.00007698384,0.000007089729,0.0002617633,0.00001992853,0.0001139985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02292086,"threshold_uncertainty_score":0.5270395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02067041235750669,"score_gpt":0.2879347834479615,"score_spread":0.2672643710904548,"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."}}