{"id":"W2223119478","doi":"10.1093/nar/gkv1115","title":"Integrated interactions database: tissue-specific view of the human and model organism interactomes","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":268,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; Queen's University; University Health Network","funders":"","keywords":"Biology; Model organism; Organism; Computational biology; Protein–protein interaction; Genome; Database; Gene; Set (abstract data type); Human proteins; Genetics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006468231,0.002196906,0.001825306,0.005457466,0.0006837666,0.002517186,0.002367763,0.001420723,0.04657074],"category_scores_gemma":[0.001872442,0.0009913477,0.001246329,0.005790888,0.0001956713,0.00191426,0.002564026,0.001398448,0.02784301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008822276,"about_ca_system_score_gemma":0.001595806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004680567,"about_ca_topic_score_gemma":0.008626355,"domain_scores_codex":[0.9996265,0.00003896231,0.00004773335,0.0001234838,0.0001157362,0.00004749667],"domain_scores_gemma":[0.999366,0.0001705539,0.00008064773,0.0001515966,0.00009750208,0.0001337418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001068672,0.0001040779,0.004025223,0.004894071,0.0005142374,0.0008416909,0.0003400369,0.002814385,0.03116204,0.01181973,0.8839314,0.0584844],"study_design_scores_gemma":[0.0002593365,0.00006145465,0.0106451,0.0005084123,0.0002736325,0.001682748,0.0001506378,0.009623105,0.009835695,0.01533486,0.9515108,0.0001142689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.003512191,0.003379796,0.03550439,0.0003977289,0.0001218852,0.0001162515,0.9054946,0.0416835,0.009789634],"genre_scores_gemma":[0.01282598,0.002457063,0.03793738,0.0002833566,0.00004457569,0.0002802574,0.9401812,0.00297074,0.003019441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04657074,"threshold_uncertainty_score":0.1557947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07572873190828375,"score_gpt":0.3607252206903182,"score_spread":0.2849964887820344,"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."}}