{"id":"W3196705307","doi":"10.1021/acs.jproteome.1c00490","title":"Extensive and Accurate Benchmarking of DIA Acquisition Methods and Software Tools Using a Complex Proteomic Standard","year":2021,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Workflow; Software; Benchmarking; Data mining; Proteomics; Quantitative proteomics; Proteome; Bioinformatics; Database; Chemistry; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001605328,0.0001253112,0.0003845218,0.0001602491,0.000224929,0.000119679,0.0001572818,0.0001174009,0.0001516798],"category_scores_gemma":[0.0008137816,0.0001145545,0.00007101567,0.0003004438,0.0002299448,0.0002954435,0.0002858654,0.0006641044,2.184451e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001412474,"about_ca_system_score_gemma":0.0003099173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007869415,"about_ca_topic_score_gemma":7.197762e-7,"domain_scores_codex":[0.9982782,0.0002092584,0.000539603,0.0002384261,0.0004539277,0.0002805944],"domain_scores_gemma":[0.9970839,0.0003779252,0.0004374794,0.0002414564,0.001721985,0.000137258],"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":[0.0001488602,0.00002768326,0.0002731566,0.0003348821,0.00003623841,0.00003177984,0.0001315616,0.00002092912,0.973951,0.0001794002,0.00001861136,0.02484585],"study_design_scores_gemma":[0.0005128029,0.0001450533,0.0007696588,0.0005763772,0.00002194741,0.0004260117,0.0002977457,0.0005751512,0.9757065,0.02041752,0.0004257802,0.0001254489],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6426058,0.0006006138,0.3560303,0.0002363439,0.000007982569,0.0003719032,0.00004274515,0.000009829135,0.00009450523],"genre_scores_gemma":[0.2400607,0.0005140367,0.7592157,0.00001022698,0.0001092865,0.00004323523,0.000004861708,0.00001952762,0.00002241454],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4031854,"threshold_uncertainty_score":0.4671395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1608773151448786,"score_gpt":0.4830560024603403,"score_spread":0.3221786873154617,"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."}}