{"id":"W4393285653","doi":"10.1007/978-1-0716-3646-6_4","title":"Data-Independent Acquisition Peptidomics","year":2024,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pipeline (software); Workflow; Computer science; Throughput; Protocol (science); Data acquisition; Data mining; Matching (statistics); Real-time computing; Database; Operating system","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":[0.001469199,0.001794082,0.001081127,0.0007894885,0.0006494595,0.001805741,0.001751415,0.001165949,0.007648834],"category_scores_gemma":[0.002743168,0.0007992531,0.000564665,0.0009414644,0.0006132021,0.001923544,0.002464921,0.002599475,0.005979494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004821522,"about_ca_system_score_gemma":0.001570138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003671064,"about_ca_topic_score_gemma":0.0009037124,"domain_scores_codex":[0.9982197,0.0001664208,0.0001133738,0.0005267405,0.0008142977,0.0001594108],"domain_scores_gemma":[0.9982279,0.0004462565,0.0001400211,0.0005017086,0.0005762505,0.0001077525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001500444,0.000129191,0.001140598,0.0008656157,0.0001671113,0.0001835117,0.0001146724,0.0007047947,0.8228453,0.004290062,0.01464617,0.1534127],"study_design_scores_gemma":[0.0001222055,0.0002104397,0.002554989,0.00005346371,0.00007196009,0.0007123506,0.00003762366,0.02265805,0.9198836,0.003327131,0.05026733,0.0001009093],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05202625,0.002601179,0.9053802,0.00121378,0.0008623108,0.0006492431,0.00686701,0.0176337,0.01276644],"genre_scores_gemma":[0.2386135,0.002031032,0.7173289,0.001992079,0.0005486333,0.001628176,0.01616345,0.003212593,0.01848161],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007648834,"threshold_uncertainty_score":0.02558786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03653417789160042,"score_gpt":0.4446703254315251,"score_spread":0.4081361475399247,"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."}}