{"id":"W4238766780","doi":"10.1074/mcp.s800108-mcp200","title":"Program","year":2009,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computational biology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008334086,0.0002343011,0.0001870195,0.00004146553,0.0001246135,0.00006645569,0.0003840926,0.0001851834,0.0001354433],"category_scores_gemma":[0.00002022173,0.0002512061,0.0001481899,0.0001676558,0.00005348944,0.00006637208,0.00005789757,0.0003272053,0.00005066644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006900901,"about_ca_system_score_gemma":0.00003705212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004303708,"about_ca_topic_score_gemma":2.378888e-7,"domain_scores_codex":[0.9987282,0.00001033272,0.0002744814,0.0004202563,0.0001865221,0.000380203],"domain_scores_gemma":[0.998965,0.000005426183,0.0001175313,0.000721434,0.00006322515,0.0001273805],"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":[0.00001061211,0.000169872,0.00001753223,0.00001571755,0.000008653421,0.00002968906,0.00001507204,0.00004451993,0.9623939,0.01335423,0.00005892953,0.02388123],"study_design_scores_gemma":[0.0002203038,0.00005866105,0.000004422918,0.00001905834,0.00001547989,0.00001209006,0.000007008596,0.0008462222,0.9494181,0.03019485,0.01891391,0.0002898506],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6272084,0.0002399158,0.3437243,0.0006520067,0.00001515089,0.0009367954,0.00001085971,0.0009608085,0.0262518],"genre_scores_gemma":[0.5737192,0.00002364271,0.424826,0.0002610074,0.00006326056,0.0004543009,0.00006920382,0.00003816111,0.0005452171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08110171,"threshold_uncertainty_score":0.999994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006837671190578831,"score_gpt":0.2582248405012476,"score_spread":0.2513871693106688,"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."}}