{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001428372,0.000216663,0.0002958397,0.0008229833,0.0007077773,0.0006426849,0.0003526707,0.0003473657,0.002989267],"category_scores_gemma":[0.0006956391,0.0001711544,0.0002051931,0.001681183,0.0001803321,0.0004886129,0.0004700334,0.0002405605,0.0005990763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000445612,"about_ca_system_score_gemma":0.0003381078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002845693,"about_ca_topic_score_gemma":0.003612235,"domain_scores_codex":[0.9998069,0.00004652864,0.000008974821,0.00005728183,0.00005773076,0.00002261716],"domain_scores_gemma":[0.9996564,0.0001360226,0.0000566397,0.00004110727,0.00005781055,0.00005207747],"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":[0.00183041,0.0004222046,0.04187588,0.001255782,0.000406587,0.003973147,0.0009873279,0.1640895,0.5892415,0.07648994,0.01995294,0.09947483],"study_design_scores_gemma":[0.00009184712,0.0002702617,0.05902226,0.00005593205,0.0002355402,0.00345769,0.0007472222,0.7589043,0.09516685,0.03869843,0.04326259,0.00008706316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913112,0.002223208,0.06692926,0.0005582108,0.00003927245,0.00009601369,0.005488283,0.0006648357,0.01088894],"genre_scores_gemma":[0.9748712,0.0006627903,0.01746976,0.00003814506,0.00001535906,0.00006253363,0.004708377,0.00002370944,0.00214807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002989267,"threshold_uncertainty_score":0.01000005,"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."}}