{"id":"W2008936042","doi":"10.1002/qsar.200860108","title":"The Use of Sequence‐Derived QSPR Descriptors for Predicting Highly Connected Proteins (Hubs) in Protein–Protein Interactions","year":2009,"lang":"en","type":"article","venue":"QSAR & Combinatorial Science","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Genome British Columbia; Genome Canada","keywords":"Quantitative structure–activity relationship; Computational biology; Sequence (biology); Staphylococcus aureus; Protein sequencing; Protein–protein interaction; Chemistry; Bioinformatics; Biology; Peptide sequence; Biochemistry; Genetics; Bacteria; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009687246,0.0001886211,0.0001947704,0.00008471942,0.0004959044,0.0001403338,0.0006289367,0.000117991,0.000004737671],"category_scores_gemma":[0.003035318,0.000149367,0.00009146196,0.0004390944,0.0003526018,0.00005797205,0.0000969594,0.0001329172,0.00000276554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007494856,"about_ca_system_score_gemma":0.0003572757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001725927,"about_ca_topic_score_gemma":0.00004307207,"domain_scores_codex":[0.9981192,0.0001477255,0.0004138094,0.0004897099,0.0003508813,0.0004786819],"domain_scores_gemma":[0.9986492,0.00007092229,0.0002565396,0.000477211,0.0004378089,0.0001083492],"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":[0.0002539161,0.0000876066,0.00006294671,0.000008980315,0.000007280353,8.27367e-7,0.00005549846,0.00001296977,0.9854428,0.01116083,0.00003514418,0.002871261],"study_design_scores_gemma":[0.0006245894,0.0009731379,0.0002860044,0.00010814,0.00000585576,0.000002021714,0.00003848382,0.0002716259,0.9819351,0.006705448,0.008861844,0.0001877498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941694,0.00005112497,0.001877584,0.0003328641,0.001037944,0.002340515,0.00001652668,0.0000262671,0.0001477655],"genre_scores_gemma":[0.9956836,0.000008768585,0.003484643,0.00004157827,0.0002082805,0.0003446449,0.000007895211,0.00001393027,0.0002066596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0088267,"threshold_uncertainty_score":0.609101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04157757356799933,"score_gpt":0.2806404257670843,"score_spread":0.239062852199085,"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."}}