{"id":"W2140163842","doi":"10.1093/bioinformatics/btu178","title":"rTANDEM, an R/Bioconductor package for MS/MS protein identification","year":2014,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Bioconductor; R package; Computer science; Pipeline (software); Identification (biology); JavaScript; Interface (matter); Software; Data mining; Operating system; Programming language; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005012436,0.003673294,0.003921942,0.004943361,0.001449535,0.00470949,0.006706668,0.00190042,0.1352523],"category_scores_gemma":[0.0183035,0.001889881,0.003031519,0.004605341,0.0009811779,0.003739086,0.003733724,0.003754577,0.1783077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181369,"about_ca_system_score_gemma":0.0034206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002681146,"about_ca_topic_score_gemma":0.003231916,"domain_scores_codex":[0.9960956,0.001060972,0.0003958509,0.001305677,0.0008612418,0.0002805789],"domain_scores_gemma":[0.9947063,0.002078711,0.0008211877,0.00102139,0.001044948,0.0003274724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004928773,0.00003105875,0.001121047,0.003713686,0.0006464512,0.0002235936,0.0001515079,0.001566317,0.005787839,0.006140946,0.9480798,0.03204478],"study_design_scores_gemma":[0.0003082914,0.00009406024,0.002897463,0.000551883,0.0005045028,0.0007477965,0.00007395967,0.01366126,0.01098932,0.02820346,0.9417803,0.000187664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002426712,0.004097352,0.2626985,0.001526894,0.001269546,0.0005200225,0.3977947,0.3129505,0.01671586],"genre_scores_gemma":[0.01648268,0.002613157,0.352602,0.002215973,0.0005205409,0.002887558,0.4101065,0.1883771,0.02419454],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1352523,"threshold_uncertainty_score":0.452464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02169888587174565,"score_gpt":0.2854976449606821,"score_spread":0.2637987590889365,"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."}}