{"id":"W2899942534","doi":"10.1093/nar/gky1037","title":"IID 2018 update: context-specific physical protein–protein interactions in human, model organisms and domesticated species","year":2018,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":203,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Krembil Foundation; Canada Foundation for Innovation","keywords":"Druggability; Biology; Context (archaeology); Computational biology; Set (abstract data type); Domestication; Computer science; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003768805,0.00195849,0.002095234,0.008430366,0.0008868859,0.005398463,0.003329284,0.001742755,0.04022518],"category_scores_gemma":[0.02157407,0.001459633,0.001461413,0.005841827,0.0004117608,0.00522206,0.004962728,0.002135401,0.02378258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001842753,"about_ca_system_score_gemma":0.00333493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180638,"about_ca_topic_score_gemma":0.02490065,"domain_scores_codex":[0.9981319,0.0002235388,0.0002793492,0.0003020666,0.0009008481,0.0001623023],"domain_scores_gemma":[0.9896404,0.003630826,0.001026234,0.00155374,0.002862705,0.001286103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001332294,0.00002571582,0.001474755,0.0009975691,0.00007440501,0.00007409797,0.00004974427,0.0003926154,0.0005178936,0.0009134138,0.9495932,0.0457534],"study_design_scores_gemma":[0.00004255279,0.00001935575,0.003334954,0.0003632201,0.00006832861,0.0002602275,0.00002636213,0.0004693321,0.0004293761,0.00149046,0.9934629,0.0000328582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.003492751,0.01755854,0.01616142,0.006530127,0.006860982,0.0002529353,0.8972387,0.0234846,0.02841997],"genre_scores_gemma":[0.005453875,0.01112314,0.01761925,0.001531979,0.001384999,0.0003669318,0.9502321,0.002905709,0.009381932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04022518,"threshold_uncertainty_score":0.1345666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04413895808054608,"score_gpt":0.3310255697652285,"score_spread":0.2868866116846824,"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."}}