{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004338666,0.0001682692,0.0001849866,0.0001265531,0.0003204095,0.0001220575,0.0003230542,0.0001338934,0.0001340001],"category_scores_gemma":[0.00005243762,0.0001532574,0.00004160618,0.0002372731,0.0008236383,0.00001677288,0.0004434637,0.0004508473,0.0001252561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000492665,"about_ca_system_score_gemma":0.00009071108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003345616,"about_ca_topic_score_gemma":0.0001042118,"domain_scores_codex":[0.9985171,0.00008655745,0.0002649137,0.0003809118,0.0002553391,0.0004951729],"domain_scores_gemma":[0.9990844,0.00001350554,0.00004875396,0.0004617619,0.0002543843,0.0001372193],"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":[0.0001203373,0.0001239829,0.00007158898,0.00001664854,0.0000218908,0.000002805284,0.0003484411,0.000008362863,0.9774412,0.007802153,0.009871414,0.004171197],"study_design_scores_gemma":[0.003144158,0.001805855,0.002514915,0.0001969665,0.00001312624,0.0000369078,0.001422725,0.03651511,0.6956825,0.03401075,0.2236695,0.0009875204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910194,0.0001448135,0.003022074,0.0005786958,0.00003993129,0.0005580118,0.00002262704,0.00001619238,0.004598288],"genre_scores_gemma":[0.9946201,0.00005485649,0.0008672954,0.00008045555,0.0004409239,0.0000587951,0.0000576242,0.00003319565,0.003786773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2817587,"threshold_uncertainty_score":0.6249656,"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."}}