{"id":"W2322307947","doi":"10.1021/ac5022166","title":"Bio-Solid-Phase Extraction/Tandem Mass Spectrometry for Identification of Bioactive Compounds in Mixtures","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Ontario Innovation Trust","keywords":"Chemistry; Chromatography; Solid phase extraction; Electrospray ionization; Mass spectrometry; Elution; Tandem mass spectrometry; Monolithic HPLC column; Monolith; Immobilized enzyme; Covalent bond; Extraction (chemistry); Electrospray; Combinatorial chemistry; High-performance liquid chromatography; Organic chemistry; Enzyme; Catalysis","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":[0.0005538928,0.001622424,0.0008407435,0.001285364,0.0003592649,0.0007844151,0.0007246286,0.0008797164,0.001206783],"category_scores_gemma":[0.000503746,0.0004816637,0.0006025778,0.0006221549,0.0003005697,0.0006181874,0.0006392514,0.001078452,0.001952084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003518592,"about_ca_system_score_gemma":0.0006014099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002841124,"about_ca_topic_score_gemma":0.0007275202,"domain_scores_codex":[0.9990607,0.000145777,0.00007908572,0.0002337461,0.0004121756,0.00006854862],"domain_scores_gemma":[0.9997445,0.00007402495,0.00005605287,0.00002372577,0.00006952296,0.00003228336],"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":[0.00003662834,0.00002925585,0.0001651258,0.00007336908,0.0000160548,0.00003552484,0.000006329568,0.00007321153,0.993306,0.00006474929,0.00008439424,0.006109308],"study_design_scores_gemma":[0.00001442445,0.0001765504,0.0009749194,0.00001055688,0.00003570137,0.0003171676,0.0000109942,0.002355075,0.9912909,0.0001253641,0.004667247,0.00002111796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2300251,0.02792412,0.7238895,0.0006331844,0.0004220384,0.0014252,0.004061775,0.005055674,0.006563307],"genre_scores_gemma":[0.389412,0.01205936,0.5829021,0.001432229,0.0001823349,0.001462806,0.004695574,0.0002591356,0.00759433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001622424,"threshold_uncertainty_score":0.004037082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01288091467674333,"score_gpt":0.3220168966487792,"score_spread":0.3091359819720358,"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."}}