{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003181464,0.000304945,0.0005506616,0.00008828364,0.00008104931,0.00004933774,0.0003655624,0.0004069004,0.0007579545],"category_scores_gemma":[0.0005215428,0.0003123491,0.0003878594,0.0005444211,0.0003436469,0.0001128082,0.00003662583,0.0003894545,0.000007987985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001207468,"about_ca_system_score_gemma":0.00005264298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008207036,"about_ca_topic_score_gemma":9.748852e-7,"domain_scores_codex":[0.9977242,0.00001510886,0.0008717701,0.0005904291,0.0003566354,0.0004418631],"domain_scores_gemma":[0.9982589,0.0004966831,0.000324759,0.0005358463,0.000164568,0.0002191739],"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":[0.0001748491,0.0006230288,0.003099314,0.0006044311,0.0001566482,0.000004805755,0.00001638943,0.00001937224,0.9941025,0.0006884538,0.000358278,0.0001519118],"study_design_scores_gemma":[0.001543816,0.0000362629,0.0002334669,0.0000697342,0.0001749602,0.00001127987,0.0002007652,0.01747884,0.97436,0.00464879,0.0009065391,0.0003355657],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9182736,0.0001374963,0.02962789,0.0002872127,0.00004571195,0.0001099786,0.0001489101,0.0001153612,0.0512538],"genre_scores_gemma":[0.9979073,0.00001866894,0.0005205321,0.00003049896,0.0002755798,0.00002773099,0.0002110675,0.00003000757,0.0009786182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07963365,"threshold_uncertainty_score":0.9999329,"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."}}