{"id":"W3169612605","doi":"10.3390/separations8060084","title":"Automated Screening and Filtering Scripts for GC×GC-TOFMS Metabolomics Data","year":2021,"lang":"en","type":"article","venue":"Separations","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Genome Alberta; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation; Genome Canada","keywords":"Mass spectrometry; Chemistry; Metabolomics; Gas chromatography; Mass spectrum; Chromatography; Mass; Resolution (logic); Scripting language; Electron ionization; Gas chromatography–mass spectrometry; Analytical Chemistry (journal); Ionization; Ion; Computer science; Organic chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005915299,0.004176451,0.001356059,0.003655896,0.001276641,0.002051941,0.002248666,0.0009158358,0.0387385],"category_scores_gemma":[0.01775178,0.0015794,0.001648135,0.001943992,0.0008224044,0.001753319,0.001687064,0.001615291,0.01782242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420891,"about_ca_system_score_gemma":0.002558982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002537273,"about_ca_topic_score_gemma":0.002509664,"domain_scores_codex":[0.9968414,0.0005702178,0.0007337041,0.0008213563,0.0007382369,0.0002950983],"domain_scores_gemma":[0.982796,0.009283607,0.001878864,0.001717395,0.003471394,0.0008527355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005733162,0.001400341,0.01696396,0.003173532,0.0005337566,0.004336835,0.002855949,0.008431504,0.1948382,0.006899115,0.2577987,0.4970348],"study_design_scores_gemma":[0.001013148,0.0009141617,0.02807605,0.0005789535,0.0002948687,0.002466655,0.0006053851,0.2019934,0.4927272,0.01047567,0.2601181,0.000736548],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01757597,0.0002242749,0.3961298,0.0002197583,0.0001557793,0.002361165,0.02379076,0.5560895,0.003453053],"genre_scores_gemma":[0.05531367,0.0003902934,0.8010299,0.0006670637,0.0001587175,0.006474471,0.0548356,0.07253214,0.008598221],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.0387385,"threshold_uncertainty_score":0.1295933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0577787569908453,"score_gpt":0.3337905097954403,"score_spread":0.276011752804595,"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."}}