{"id":"W2092415108","doi":"10.1021/pr0707509","title":"Open Access to Proteomics Data: A Valuable Resource for Biology and Medicine","year":2007,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of California, Los Angeles; School of Medicine, Vanderbilt University; Rijksuniversiteit Groningen; Imperial College London; McGill University; University of Ottawa; National Cancer Institute; Carnegie Mellon University; Université de Genève; Yale University; Vanderbilt University; Purdue University; North Carolina State University; Bristol-Myers Squibb; AstraZeneca; Lunds Universitet; Johns Hopkins University; Pfizer","keywords":"Proteomics; Resource (disambiguation); Computational biology; Data science; Computer science; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.02659683,0.00216243,0.004719102,0.02042405,0.003042442,0.02594375,0.007913556,0.008938327,0.07477417],"category_scores_gemma":[0.1222539,0.002037725,0.002038723,0.02452496,0.004628695,0.02679556,0.0283466,0.01147476,0.0901487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004066791,"about_ca_system_score_gemma":0.01392963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002017148,"about_ca_topic_score_gemma":0.001600865,"domain_scores_codex":[0.9736452,0.00554626,0.004432191,0.003480966,0.01138857,0.001506899],"domain_scores_gemma":[0.839985,0.04205333,0.01295856,0.05306057,0.02999512,0.02194736],"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":[0.0004020641,0.000126196,0.001420935,0.002978151,0.0002402731,0.0004455872,0.0003248905,0.0003299231,0.002622563,0.02021127,0.8343419,0.1365562],"study_design_scores_gemma":[0.00005311502,0.00002903939,0.001084979,0.001412615,0.000036636,0.0002613859,0.0002332541,0.0002658703,0.0006777609,0.02497894,0.9708931,0.0000733476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"commentary","genre_scores_codex":[0.004292475,0.0667293,0.1484913,0.2037889,0.03332316,0.001840231,0.3730225,0.05805153,0.1104607],"genre_scores_gemma":[0.04202835,0.06499323,0.2114941,0.07332412,0.02360437,0.00211647,0.5183896,0.02709613,0.03695374],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9920865,"threshold_uncertainty_score":0.2501445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2729485310152599,"score_gpt":0.5450953399739819,"score_spread":0.272146808958722,"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."}}