{"id":"W2078336808","doi":"10.1016/j.febslet.2012.04.027","title":"Domain‐mediated protein interaction prediction: From genome to network","year":2012,"lang":"en","type":"review","venue":"FEBS Letters","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"PDZ domain; Computational biology; Context (archaeology); Genome; Protein–protein interaction; Interaction network; Domain (mathematical analysis); Human genome; Sequence (biology); Computer science; Protein Interaction Networks; Biology; Gene; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002207467,0.0004277347,0.0006342251,0.00006574714,0.000098048,0.00006582559,0.0003442018,0.0004872046,0.00009283399],"category_scores_gemma":[0.000007514427,0.0003828979,0.0003191744,0.0001616822,0.00003539481,0.000007317801,0.0002277274,0.0003674517,0.0004518235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008677191,"about_ca_system_score_gemma":0.00005930531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001223111,"about_ca_topic_score_gemma":0.00001153472,"domain_scores_codex":[0.9982262,0.0001060394,0.0006009704,0.0004120103,0.0001449195,0.0005098617],"domain_scores_gemma":[0.9988216,0.00001833036,0.0003265151,0.0005909515,0.00002593471,0.0002166702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001582038,0.0001188541,0.00002815708,0.003535615,0.002219291,0.0000187788,0.0003025655,0.0004389141,0.00782323,0.00008911012,0.1555813,0.8296859],"study_design_scores_gemma":[0.0001277654,0.00006083232,0.0000104131,0.0008632229,0.0001824633,0.00001342232,0.000006804662,0.000002812287,0.000006200022,0.00001340316,0.9983363,0.0003763468],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004413312,0.9850791,0.01036117,0.0002368446,0.001541687,0.00137416,0.0004753213,0.00003684936,0.00045353],"genre_scores_gemma":[0.00009387334,0.9619616,0.005774948,0.003552447,0.01309393,0.0005389749,0.01450228,0.0001392747,0.0003426313],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.842755,"threshold_uncertainty_score":0.9998623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763862114389053,"score_gpt":0.2469757317210779,"score_spread":0.2293371105771874,"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."}}