{"id":"W2988310131","doi":"10.1016/j.cell.2019.10.005","title":"Cellular Senescence: Defining a Path Forward","year":2019,"lang":"en","type":"review","venue":"Cell","topic":"Telomeres, Telomerase, and Senescence","field":"Medicine","cited_by":3117,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"H2020 European Research Council; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Biotechnology and Biological Sciences Research Council; Hellenic Foundation for Research and Innovation; European Commission; National Institute on Aging; European Regional Development Fund; Horizon 2020 Framework Programme; Cancer Research UK; Medical Research Council; Social and Cultural Affairs Welfare Foundation","keywords":"Biology; Senescence; Path (computing); Cellular senescence; Cell biology; Computational biology; Genetics; Phenotype; Gene; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001288404,0.001412678,0.002080775,0.002763919,0.000544171,0.002211409,0.00121323,0.002513831,0.004898102],"category_scores_gemma":[0.001787375,0.0002982816,0.0004923407,0.002773422,0.001087737,0.002922392,0.001369318,0.004067471,0.003009302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001247998,"about_ca_system_score_gemma":0.002325227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001043474,"about_ca_topic_score_gemma":0.002881946,"domain_scores_codex":[0.9996661,0.00007514549,0.00005004084,0.00005368142,0.000120069,0.00003487708],"domain_scores_gemma":[0.9990677,0.0004730849,0.00009909071,0.00002505329,0.0002273359,0.0001077667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001254246,0.00006786567,0.0001592895,0.0169085,0.00007070715,0.0001879494,0.00009070835,0.0002911622,0.001216699,0.008937174,0.100394,0.8715505],"study_design_scores_gemma":[0.00001742463,0.00005899641,0.0002972171,0.004401,0.00006832318,0.0004254206,0.00008889328,0.00005030759,0.0001162756,0.003077621,0.9913841,0.00001447556],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002339952,0.9979661,0.00007116282,0.000694347,0.0006678248,0.000001753813,0.000009455901,0.000006026269,0.000559944],"genre_scores_gemma":[0.0002497137,0.9977794,0.0001199111,0.0006150931,0.0007071115,0.000004551131,0.00001512834,0.000001205588,0.0005078926],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004898102,"threshold_uncertainty_score":0.01638579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04590593308533635,"score_gpt":0.309153432018905,"score_spread":0.2632474989335687,"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."}}