{"id":"W2116184147","doi":"10.1002/rcm.2996","title":"MS E with mass defect filtering for in vitro and in vivo metabolite identification","year":2007,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":254,"is_retracted":false,"has_abstract":true,"ca_institutions":"Merck Canada Inc. (Canada); TransCanada (Canada)","funders":"","keywords":"Chemistry; Metabolite; Mass spectrometry; In vivo; Chromatography; Mass; Identification (biology); In vitro; Mass spectrum; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00375975,0.0003248458,0.0005010936,0.00111813,0.0002194712,0.00005847252,0.0009386061,0.000254091,0.0001126997],"category_scores_gemma":[0.0001075361,0.0003448852,0.0001135475,0.001536466,0.0002700916,0.0002215833,0.0001787451,0.00103535,0.000009264724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001766645,"about_ca_system_score_gemma":0.00006351394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000415937,"about_ca_topic_score_gemma":0.0001009347,"domain_scores_codex":[0.9971033,0.0005648092,0.0008510045,0.0005145121,0.0001897892,0.0007765813],"domain_scores_gemma":[0.9972402,0.001260479,0.0002256922,0.001017925,0.0000795158,0.0001761327],"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":[0.0008257725,0.0004943706,0.0166712,0.00007701165,0.0001180476,0.00001219126,0.0008353381,0.002213881,0.9668601,0.002487439,0.00007547422,0.009329228],"study_design_scores_gemma":[0.008344037,0.0001007313,0.01991738,0.00005552451,0.0002730403,0.00003646265,0.0009322896,0.04536564,0.8205906,0.00485176,0.09863623,0.0008962735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9477533,0.02365584,0.01536617,0.001313471,0.0002952849,0.001781204,0.0002508047,0.00009960332,0.009484352],"genre_scores_gemma":[0.9530907,0.008605182,0.03706705,0.0005456938,0.00009541336,0.0003237019,0.00007460313,0.00005174541,0.0001458894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1462694,"threshold_uncertainty_score":0.9999003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05996671794945838,"score_gpt":0.3859389317189198,"score_spread":0.3259722137694614,"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."}}