{"id":"W4403763048","doi":"10.1101/2024.10.25.620155","title":"Mitochondrial ETF insufficiency drives neoplastic growth by selectively optimizing cancer bioenergetics","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"ATP Synthase and ATPases Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto; Université de Montréal; The Metabolomics Innovation Centre; McGill University Health Centre; Queen's University; McGill University and Génome Québec Innovation Centre; Hospital for Sick Children; Institute for Research in Immunology and Cancer; McGill University","funders":"Vetenskapsrådet; Terry Fox Foundation","keywords":"Bioenergetics; Reduction (mathematics); Expression (computer science); Computer science; Biology; Cell biology; Mathematics","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":[0.0001283949,0.0002168405,0.0002514159,0.0002815379,0.0001838243,0.0005183927,0.0002060942,0.0003956421,0.00306687],"category_scores_gemma":[0.0001547611,0.0001508542,0.0001838059,0.0002349021,0.0002914762,0.0002372436,0.0004003574,0.0005820562,0.0007986329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004581799,"about_ca_system_score_gemma":0.0001940928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006635816,"about_ca_topic_score_gemma":0.0007772423,"domain_scores_codex":[0.99986,0.00001281689,0.00001228694,0.00004431011,0.00004143673,0.00002901049],"domain_scores_gemma":[0.9998518,0.00002706858,0.00003599902,0.00002583158,0.0000132194,0.00004604278],"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":[0.00014855,0.00001844727,0.0005867425,0.000034968,0.000006226023,0.00009604748,0.00001660105,0.0001177307,0.9966181,0.000357438,0.0002109728,0.001788325],"study_design_scores_gemma":[0.00001769244,0.0000643399,0.003957602,0.000008018229,0.00001048334,0.0003355856,0.00004578038,0.001244316,0.9885028,0.0001885622,0.005619646,0.00000510064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846023,0.001880073,0.005938123,0.0003818889,0.00008331844,0.00002918322,0.002681797,0.0004114216,0.003991823],"genre_scores_gemma":[0.9918584,0.0005943067,0.001735791,0.00005970525,0.000007619051,0.00001914279,0.001096289,0.00008353,0.00454527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00306687,"threshold_uncertainty_score":0.01025969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009272937752913324,"score_gpt":0.2479924574662858,"score_spread":0.2387195197133725,"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."}}