{"id":"W6892537485","doi":"10.5281/zenodo.10718844","title":"shorvath/MammalianMethylationConsortium: Lifespan Predictors","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tellabs (Canada)","funders":"","keywords":"Life history; Disease; Population; Data collection","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":[0.00277735,0.003460474,0.002411009,0.002438126,0.0007458001,0.001852877,0.003359697,0.001179762,0.1878774],"category_scores_gemma":[0.009725049,0.002268645,0.002469744,0.001970413,0.0006821231,0.001687894,0.003072955,0.002033504,0.1679767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005517264,"about_ca_system_score_gemma":0.001547446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003363889,"about_ca_topic_score_gemma":0.006197039,"domain_scores_codex":[0.9984612,0.0003887374,0.0001357011,0.000560119,0.0002804326,0.0001738049],"domain_scores_gemma":[0.9970746,0.001517916,0.0002845929,0.0006973728,0.00021686,0.0002087887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007353824,0.00005349487,0.008835788,0.001856823,0.0006263248,0.0002107663,0.0003013646,0.002948329,0.005422959,0.003795351,0.9186668,0.0565465],"study_design_scores_gemma":[0.0008519571,0.0002511552,0.01971556,0.0003549985,0.0006367629,0.0008147662,0.0001078262,0.0218772,0.02999832,0.02029067,0.9046738,0.0004270534],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005731171,0.0009480875,0.1150356,0.0005816226,0.0005396217,0.0002121361,0.4700472,0.396499,0.01040549],"genre_scores_gemma":[0.05002679,0.00054932,0.185521,0.001190247,0.0002368952,0.00294734,0.400053,0.3320332,0.02744219],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1878774,"threshold_uncertainty_score":0.6285127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03431448765975592,"score_gpt":0.2617453542882809,"score_spread":0.227430866628525,"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."}}