{"id":"W1969651225","doi":"10.1021/acs.analchem.5b00170","title":"Picodiscs for Facile Protein-Glycolipid Interaction Analysis","year":2015,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Alberta Glycomics Centre; University Health Network","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Alberta Glycomics Centre; Canadian Institutes of Health Research; National Science Council","keywords":"Glycolipid; Chemistry; Electrospray ionization; Hydrolysis; Biochemistry; Mass spectrometry; Sphingolipid; Enzyme; Electrospray mass spectrometry; Chromatography; Electrospray","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":[],"consensus_categories":[],"category_scores_codex":[0.0001236735,0.0001572328,0.000202371,0.00002761158,0.00004436396,0.00003622123,0.0001723303,0.000206207,0.00004631087],"category_scores_gemma":[0.0004188636,0.0001452625,0.0002464507,0.0001969212,0.00006223437,0.000005190763,0.00007746905,0.00009964476,0.000008150104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003614504,"about_ca_system_score_gemma":0.0001127898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009843307,"about_ca_topic_score_gemma":0.000008392626,"domain_scores_codex":[0.9990268,0.00001249739,0.0002090391,0.0003667924,0.0001455656,0.0002392813],"domain_scores_gemma":[0.9991255,0.00000901503,0.00006970554,0.0003670903,0.0001642359,0.0002643906],"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":[0.0009847961,0.0002497107,0.004225315,0.0001967546,0.002296765,0.000009656791,0.00006010844,0.002170594,0.9655018,0.00071455,0.0208515,0.002738472],"study_design_scores_gemma":[0.001380903,0.0002686118,0.0001679087,0.00001278466,0.0008680423,0.00002039787,0.0002292989,0.026183,0.7830097,0.001605241,0.1856012,0.0006528618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.908049,0.0001473835,0.07480121,0.0004229959,0.00008736069,0.0003803227,0.0001147948,0.00004109085,0.01595581],"genre_scores_gemma":[0.9920943,0.000003337057,0.001354123,0.0001552903,0.0004072827,0.0000697431,0.0006249449,0.00001518795,0.005275799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1824921,"threshold_uncertainty_score":0.5923634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829821493152678,"score_gpt":0.2886410012201353,"score_spread":0.2703427862886085,"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."}}