{"id":"W2521489910","doi":"10.1101/074567","title":"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"Core Research for Evolutional Science and Technology; National Cancer Institute; National Human Genome Research Institute; National Institute of General Medical Sciences; Functional Genomics Center Zurich; SystemsX.ch; National Institutes of Health; Ontario Genomics; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Australian Government; Japan Agency for Medical Research and Development; National Science Foundation; Canadian Institutes of Health Research; Genome Canada; Buck Institute for Research on Aging; Government of Canada","keywords":"Reproducibility; Quantitative proteomics; Proteomics; Proteome; Computer science; Mass spectrometry; Label-free quantification; Data mining; Computational biology; Bioinformatics; Chemistry; Chromatography; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03780191,0.001461606,0.00114767,0.001973816,0.001244952,0.002050143,0.001223586,0.001323462,0.0008953887],"category_scores_gemma":[0.02483962,0.0005175393,0.0009461044,0.002086442,0.001810477,0.000826249,0.00191832,0.0009266739,0.0007532467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007831324,"about_ca_system_score_gemma":0.0007150914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001363213,"about_ca_topic_score_gemma":0.001114405,"domain_scores_codex":[0.9557135,0.01572776,0.004137562,0.006509231,0.01706629,0.0008456418],"domain_scores_gemma":[0.9577808,0.01221933,0.005897401,0.008963199,0.01442786,0.0007113403],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003576857,0.002318919,0.07205655,0.0005961772,0.001532434,0.0002345885,0.001586454,0.007390792,0.8581143,0.0006299376,0.001366408,0.05059651],"study_design_scores_gemma":[0.0001216106,0.007567245,0.1263916,0.00006043922,0.0007652707,0.0006474009,0.0004173696,0.02020693,0.8379002,0.000500442,0.005227237,0.0001943094],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8329306,0.001521479,0.1575198,0.0002235541,0.0002643299,0.001150027,0.002050702,0.001200382,0.003139188],"genre_scores_gemma":[0.9272773,0.0002789873,0.06617951,0.0001935958,0.00007532156,0.001270187,0.002449737,0.0004135709,0.001861847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9621981,"threshold_uncertainty_score":0.199918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03172893622031354,"score_gpt":0.3307302227908983,"score_spread":0.2990012865705847,"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."}}