{"id":"W3081885424","doi":"10.1016/j.cmet.2020.07.017","title":"A High-Density Human Mitochondrial Proximity Interaction Network","year":2020,"lang":"en","type":"article","venue":"Cell Metabolism","topic":"Mitochondrial Function and Pathology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":211,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Lunenfeld-Tanenbaum Research Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada Foundation for Innovation; Government of Ontario; Canadian Institutes of Health Research; Ontario Genomics; United Mitochondrial Disease Foundation; Genome Canada","keywords":"Computational biology; Biology; Mitochondrion; Cell biology; Computer science","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":[0.0000777547,0.0001836984,0.0002409603,0.00001957506,0.000148047,0.00003086366,0.0001649044,0.0002169745,0.0002981874],"category_scores_gemma":[0.00007965329,0.0001798137,0.0001410011,0.0001080458,0.00004848473,0.000007576171,0.0001249315,0.000213584,0.0001522815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000549281,"about_ca_system_score_gemma":0.00003181507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003509761,"about_ca_topic_score_gemma":0.00002798744,"domain_scores_codex":[0.9987438,0.0001729338,0.0002377147,0.0004781666,0.0001086492,0.0002586896],"domain_scores_gemma":[0.9993309,0.000008057977,0.000118751,0.000292216,0.00007572023,0.0001742959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002536561,0.00004003163,0.000133079,0.00001067214,0.000018825,0.000005100871,0.00006547278,0.00009666439,0.9443783,0.0006554566,0.0539732,0.00036954],"study_design_scores_gemma":[0.001269113,0.0002071973,0.001152302,0.000003005665,0.00006353625,0.00001013397,0.00002996105,0.00003107926,0.495715,0.000287041,0.5009633,0.0002683661],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720976,0.0003178649,0.01625381,0.0005623257,0.00633135,0.000411418,0.00001342524,0.00007141253,0.00394076],"genre_scores_gemma":[0.9760718,0.00006083549,0.004909909,0.003164388,0.01353514,0.00003225238,0.0002602586,0.00003744024,0.001927958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4486633,"threshold_uncertainty_score":0.7332588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636487656195433,"score_gpt":0.2382578499178488,"score_spread":0.2218929733558944,"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."}}