{"id":"W2955656412","doi":"10.12688/f1000research.17196.1","title":"mTOR as a central regulator of lifespan and aging","year":2019,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Autophagy in Disease and Therapy","field":"Medicine","cited_by":437,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; Université de Montréal; Hôpital Maisonneuve-Rosemont; McGill University; Jewish General Hospital","funders":"Lady Davis Institute for Medical Research; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Terry Fox Research Institute; Azrieli Foundation; Israel Science Foundation; International Development Research Centre","keywords":"Proteostasis; Autophagy; PI3K/AKT/mTOR pathway; Regulator; Cell biology; Biology; Mechanistic target of rapamycin; Nutrient sensing; mTORC2; Senescence; Neuroscience; Cellular senescence; Longevity; Cell metabolism; Cell; mTORC1; Signal transduction; Phenotype; Apoptosis; Genetics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003644266,0.0002012834,0.0005107148,0.0001920869,0.00004029607,0.00003316974,0.0002382671,0.0002601627,0.000941462],"category_scores_gemma":[0.0001564458,0.0001763927,0.0001594924,0.0001145574,0.0002017992,0.00003403098,0.0006255974,0.0007412338,0.00009484758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008054445,"about_ca_system_score_gemma":0.0009557609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002174898,"about_ca_topic_score_gemma":0.000001615514,"domain_scores_codex":[0.99799,0.0001007763,0.0002811613,0.0004481128,0.0007083544,0.0004716171],"domain_scores_gemma":[0.9984279,0.0001055411,0.0000934304,0.0008003589,0.0001826346,0.000390166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009337301,0.002887988,0.6625859,0.0295217,0.005926617,0.002003415,0.01043651,0.0002332098,0.1036303,0.01260211,0.05892408,0.1019109],"study_design_scores_gemma":[0.00541765,0.001029151,0.8695645,0.003564074,0.0003623265,0.0001001834,0.0004978651,0.00311399,0.07825754,0.007345924,0.03004182,0.0007049603],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860143,0.007022385,0.00002600433,0.00136707,0.0002584013,0.001076811,0.00006072463,0.00005812623,0.004116151],"genre_scores_gemma":[0.9865251,0.001509657,0.000216071,0.0002031342,0.0004675851,0.00003546842,0.00007680013,0.0000581599,0.01090805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2069786,"threshold_uncertainty_score":0.9999718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159732065198435,"score_gpt":0.3683454684601126,"score_spread":0.3367481478081283,"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."}}