{"id":"W2146764011","doi":"10.1016/s1672-0229(08)60005-4","title":"Prediction of Protein-Protein Interactions Using Protein Signature Profiling","year":2007,"lang":"en","type":"article","venue":"Genomics Proteomics & Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"PDZ domain; Receiver operating characteristic; Biology; Protein domain; Computational biology; Protein–protein interaction; Structural similarity; Genetics; Computer science; Artificial intelligence; Gene; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00120567,0.000451529,0.0004045902,0.0003242133,0.0002660492,0.0000884709,0.000501445,0.0005402478,0.00001283978],"category_scores_gemma":[0.00009679458,0.0004583988,0.0002428979,0.0003756829,0.0001831691,0.00005867235,0.0003543511,0.0005722477,0.00001702363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001718705,"about_ca_system_score_gemma":0.0003663203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001956232,"about_ca_topic_score_gemma":0.0000172612,"domain_scores_codex":[0.9970173,0.00003792878,0.00158242,0.0003332932,0.0003126269,0.0007164415],"domain_scores_gemma":[0.9976321,0.00001110023,0.001004017,0.000784043,0.0003563879,0.0002122916],"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":[0.0002692649,0.00008469968,0.00008905862,0.0003081608,0.0001199474,0.000001288629,0.0004189924,0.00136498,0.9918408,0.001411938,0.00004439479,0.004046457],"study_design_scores_gemma":[0.0009807752,0.0003827296,0.00005055607,0.0002096871,0.00004796039,0.00005029935,0.0006030956,0.04679278,0.9446417,0.001403091,0.004317694,0.0005196116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6464361,0.0001478919,0.3489859,0.00002526212,0.0001972645,0.002714029,0.0001840026,0.00003498095,0.001274509],"genre_scores_gemma":[0.6492206,0.00001542927,0.3495437,0.00007767681,0.0003809161,0.00007704962,0.000329849,0.00006263247,0.0002920643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0471991,"threshold_uncertainty_score":0.9997868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509141778472642,"score_gpt":0.2393423018496557,"score_spread":0.2242508840649293,"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."}}