{"id":"W4224089232","doi":"10.1007/s11306-022-01881-z","title":"Evaluation of fresh, frozen, and lyophilized fecal samples by SPME and derivatization methods using GC×GC-TOFMS","year":2022,"lang":"en","type":"article","venue":"Metabolomics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Outotec (Canada); University of Alberta","funders":"Genome Alberta; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation; Genome Canada","keywords":"Derivatization; Chromatography; Metabolome; Chemistry; Sample preparation; Mass spectrometry; Gas chromatography–mass spectrometry; Gas chromatography; Metabolomics; Solid-phase microextraction; Metabolite; Feces; Lysis; Biochemistry; Microbiology; 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":[0.002332073,0.000175138,0.000352845,0.00009065104,0.0002367881,0.00002282172,0.0001120136,0.00008022531,0.00007212513],"category_scores_gemma":[0.0005110151,0.0001778211,0.00005822962,0.0001655027,0.0001184146,0.00000744893,0.0003798663,0.00009564782,1.207202e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000269301,"about_ca_system_score_gemma":0.00007497992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006040211,"about_ca_topic_score_gemma":0.000013192,"domain_scores_codex":[0.9981743,0.0006049763,0.0003206196,0.0003964316,0.0003119406,0.000191713],"domain_scores_gemma":[0.9992668,0.00004399428,0.0002164059,0.0002396682,0.0001801245,0.0000530196],"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":[0.00006127468,0.00004699995,0.002478561,0.00001353899,0.0001873142,1.249757e-7,0.00008583509,0.0002417928,0.9867283,0.0006249844,0.0003386637,0.009192593],"study_design_scores_gemma":[0.004353547,0.000413151,0.01117878,0.000007218978,0.001391254,0.00004790905,0.001117066,0.02573065,0.8851009,0.006807635,0.0631282,0.0007236957],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9496109,0.02679994,0.02275859,0.00008644286,0.0002004148,0.0002848236,0.0001669799,0.000006803638,0.00008511457],"genre_scores_gemma":[0.9310468,0.002784999,0.06562472,0.0001241133,0.00008130955,0.00004251654,0.0002256189,0.00002909438,0.0000407921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1016274,"threshold_uncertainty_score":0.7251334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04713025040300667,"score_gpt":0.335787913449329,"score_spread":0.2886576630463223,"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."}}