{"id":"W2105869274","doi":"10.1002/rcm.525","title":"<sup>18</sup> O Labeling: a tool for proteomics","year":2001,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":328,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada","funders":"","keywords":"Chemistry; Peptide; Trypsin; Quantitative proteomics; Linear relationship; Chromatography; Detection limit; Proteomics; Enzyme; Biochemistry; Statistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008701663,0.0008472892,0.0003239571,0.00039445,0.0003790991,0.0006049789,0.0009134084,0.0007695789,0.003655752],"category_scores_gemma":[0.0007620931,0.0002785186,0.0002630153,0.0005873204,0.0006730022,0.0007682575,0.0003869167,0.0007804374,0.00369706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002694329,"about_ca_system_score_gemma":0.0002681127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003182628,"about_ca_topic_score_gemma":0.0005685994,"domain_scores_codex":[0.9996198,0.00007621186,0.00002606923,0.00004949972,0.0001966826,0.00003154412],"domain_scores_gemma":[0.9994947,0.0001798848,0.0001135071,0.00005699207,0.0001176461,0.0000372578],"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":[0.0001649293,0.00002308764,0.0003541514,0.0003097054,0.000009989379,0.0001932747,0.00002726238,0.0001581532,0.9735571,0.0006343214,0.001543162,0.02302491],"study_design_scores_gemma":[0.00001108592,0.0002983707,0.002116594,0.00005731602,0.00003284271,0.00134131,0.00005518313,0.001656326,0.9438648,0.0007333737,0.04981504,0.00001776902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2982929,0.04799953,0.6025273,0.004071591,0.001912191,0.0006310875,0.003438998,0.004555498,0.03657092],"genre_scores_gemma":[0.2836625,0.02760113,0.6585556,0.001893857,0.000441634,0.0006273768,0.00329899,0.001082328,0.02283657],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003655752,"threshold_uncertainty_score":0.01222974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03623277268844937,"score_gpt":0.3226549953876611,"score_spread":0.2864222226992117,"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."}}