{"id":"W2005267401","doi":"10.1093/nar/gkn161","title":"Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach","year":2008,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Genome Canada","keywords":"SH2 domain; Computational biology; Biology; Colocalization; Bioinformatics; Proto-oncogene tyrosine-protein kinase Src; Genetics; Phosphorylation; Cell 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":[],"consensus_categories":[],"category_scores_codex":[0.0003841904,0.000821784,0.0005073391,0.001394931,0.0003251924,0.0004399065,0.0005096202,0.0004504875,0.001683847],"category_scores_gemma":[0.0009023203,0.0003049969,0.0006664073,0.0005212886,0.0001976503,0.0003908477,0.0003060464,0.0004237304,0.0004088043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004853836,"about_ca_system_score_gemma":0.0007959673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002745573,"about_ca_topic_score_gemma":0.003919784,"domain_scores_codex":[0.9998478,0.0000553367,0.000009006011,0.00002862342,0.00004257692,0.00001661366],"domain_scores_gemma":[0.9996686,0.0001930023,0.00003819698,0.00001434563,0.00005469201,0.00003113188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000612861,0.0003749575,0.009042476,0.0002392149,0.0001981458,0.0004460566,0.00007315094,0.6856793,0.1165597,0.008053267,0.003108043,0.1756129],"study_design_scores_gemma":[0.00001195083,0.00004582881,0.0005235395,0.000002027223,0.000007588169,0.0000479235,0.000005764412,0.9941456,0.003741295,0.001132356,0.0003313173,0.00000467276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1832337,0.0002481086,0.8109618,0.0001406935,0.00001088567,0.0001326521,0.0007357828,0.003287908,0.0012486],"genre_scores_gemma":[0.6165934,0.000208219,0.3800957,0.00004419733,0.00001475022,0.0002404632,0.001634042,0.00006477797,0.00110449],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002745573,"threshold_uncertainty_score":0.005633056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1648055275577826,"score_gpt":0.37397016662463,"score_spread":0.2091646390668474,"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."}}