{"id":"W1968063944","doi":"10.1021/pr9006365","title":"Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry","year":2009,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":562,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Cancer Institute; U.S. Public Health Service","keywords":"Repeatability; Reproducibility; Chromatography; Proteomics; Biomarker discovery; Tandem mass spectrometry; Peptide; Proteome; Chemistry; Orbitrap; Mass spectrometry; Label-free quantification; Quantitative proteomics; Liquid chromatography–mass spectrometry; Computational biology; Biology; Biochemistry","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0520829,0.001179556,0.001414666,0.003615944,0.001603902,0.003271973,0.001982604,0.001220745,0.0006636325],"category_scores_gemma":[0.07780124,0.001071033,0.001635558,0.003292858,0.00272511,0.001887888,0.002870237,0.001478579,0.0005375415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099893,"about_ca_system_score_gemma":0.0009035583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00141642,"about_ca_topic_score_gemma":0.002970961,"domain_scores_codex":[0.8995747,0.03156155,0.01178201,0.01470513,0.04067253,0.001704079],"domain_scores_gemma":[0.9256693,0.03709275,0.006965308,0.01855098,0.01136679,0.0003549388],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001629755,0.0006451836,0.1919965,0.001635725,0.002913203,0.0007046689,0.003549627,0.008932371,0.6537999,0.003536807,0.001763834,0.1288925],"study_design_scores_gemma":[0.00006311604,0.002434821,0.339847,0.000266795,0.001076399,0.001962826,0.001034056,0.02527565,0.6077875,0.007066051,0.01272565,0.0004603143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6331674,0.008245924,0.3461949,0.0007589307,0.000567904,0.0009532094,0.002108568,0.001508646,0.006494518],"genre_scores_gemma":[0.8588002,0.001232451,0.1332095,0.0005949929,0.0001511738,0.0008953328,0.003064626,0.0006434118,0.001408263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9479171,"threshold_uncertainty_score":0.275444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03830414990698112,"score_gpt":0.3766268700147317,"score_spread":0.3383227201077506,"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."}}