{"id":"W2318076112","doi":"10.1021/ac202760e","title":"Applications of a Catch and Release Electrospray Ionization Mass Spectrometry Assay for Carbohydrate Library Screening","year":2011,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Glycomics Centre; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Glycomics Centre; University of Alberta","keywords":"Chemistry; Electrospray ionization; Mass spectrometry; Carbohydrate; Chromatography; Electrospray; Dissociation (chemistry); Deprotonation; Mass spectrum; Ligand (biochemistry); Collision-induced dissociation; Ion; Tandem mass spectrometry; Biochemistry; Organic chemistry","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":[0.0006763664,0.001160761,0.000520123,0.001027889,0.000288194,0.000767481,0.0008187629,0.0009699779,0.001048202],"category_scores_gemma":[0.00101043,0.0003255972,0.0004215936,0.0007091144,0.0003688181,0.0004117207,0.0008636289,0.001006947,0.0009409421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003995055,"about_ca_system_score_gemma":0.0004091002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003249968,"about_ca_topic_score_gemma":0.0006042018,"domain_scores_codex":[0.9988444,0.0001619053,0.00006500632,0.0001908145,0.0006451803,0.00009276465],"domain_scores_gemma":[0.9993851,0.0001791984,0.0001057926,0.00005634362,0.0001621853,0.000111414],"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":[0.00002213588,0.00003985127,0.0001845898,0.00004243405,0.000007316442,0.00004747663,0.000008148751,0.0001150882,0.9946678,0.00008271381,0.00009346541,0.004688981],"study_design_scores_gemma":[0.000009406394,0.0002449103,0.001013264,0.00000891181,0.0000142075,0.0004927727,0.00001427042,0.002921723,0.9927013,0.0001181581,0.002445931,0.00001520989],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4185059,0.007009242,0.5594457,0.0007176218,0.0002662739,0.00145104,0.001098954,0.003704156,0.007801178],"genre_scores_gemma":[0.5673081,0.007808879,0.4132146,0.0008758341,0.0001100293,0.001396382,0.001567328,0.0002002468,0.007518672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001160761,"threshold_uncertainty_score":0.003576994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268252542336044,"score_gpt":0.2414519330296488,"score_spread":0.2287694076062884,"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."}}