{"id":"W2093966983","doi":"10.1002/cbic.200700674","title":"An ESI‐MS/MS Method for Screening of Small‐Molecule Mixtures against Glycogen Synthase Kinase‐3β (GSK‐3β)","year":2008,"lang":"en","type":"article","venue":"ChemBioChem","topic":"Wnt/β-catenin signaling in development and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Chemistry; Substrate (aquarium); GSK-3; Glycogen synthase; Peptide; Electrospray ionization; Phosphorylation; Mass spectrometry; GSK3B; Enzyme; Hyperphosphorylation; Chromatography; Tandem mass spectrometry; Kinase; Small molecule; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001151719,0.001647894,0.0005724906,0.0009990985,0.0004105404,0.0004222222,0.0007947944,0.001018118,0.002253907],"category_scores_gemma":[0.001376395,0.0004966389,0.0003623629,0.0006971642,0.0004698313,0.0006937817,0.0007359065,0.001379554,0.001848055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005090391,"about_ca_system_score_gemma":0.0009368971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004022553,"about_ca_topic_score_gemma":0.0007377076,"domain_scores_codex":[0.9989036,0.000188404,0.00007243478,0.0002707048,0.0005116641,0.00005314256],"domain_scores_gemma":[0.9992815,0.0002438584,0.0001524828,0.00004205569,0.0001737437,0.0001064047],"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":[0.00008982896,0.00004259396,0.0001780633,0.0001086115,0.0000273931,0.00006096057,0.00001346826,0.0001430295,0.9906777,0.0001648647,0.0003422676,0.008151117],"study_design_scores_gemma":[0.00003602848,0.0003595924,0.0009424287,0.00001913213,0.00004676713,0.0008042728,0.00001691349,0.003724691,0.989459,0.0001604807,0.004403328,0.0000273678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.169986,0.01181173,0.8007057,0.0007266985,0.0005886115,0.001143539,0.002747144,0.00505661,0.007234006],"genre_scores_gemma":[0.4203668,0.01036968,0.552066,0.001745701,0.000159547,0.00317463,0.003433774,0.0003309351,0.008352952],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002253907,"threshold_uncertainty_score":0.007540107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02378702925782524,"score_gpt":0.2799883559164119,"score_spread":0.2562013266585867,"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."}}