{"id":"W2154436850","doi":"10.1038/sj.embor.7400431","title":"Medicine, ageing and human longevity","year":2005,"lang":"en","type":"article","venue":"EMBO Reports","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Longevity; Ageing; Biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001947577,0.0001143982,0.0001959844,0.0001049069,0.0006615723,0.00005838123,0.0001022621,0.00006582917,0.0003398173],"category_scores_gemma":[0.0001394068,0.0001070866,0.00005305531,0.0002324127,0.0004614462,0.0002343939,0.00005810934,0.0001160245,0.00001035001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005258594,"about_ca_system_score_gemma":0.00002492946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006256418,"about_ca_topic_score_gemma":0.01194785,"domain_scores_codex":[0.9983209,0.0001108942,0.0003630335,0.0003383056,0.0005548848,0.000311994],"domain_scores_gemma":[0.9992303,0.00003048982,0.0002172113,0.0003277038,0.00006060403,0.0001336962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002203563,0.00008274547,0.8990583,0.00003675742,0.00005466135,0.001341644,0.009176821,0.00001171295,0.0000780539,0.03169379,0.0210261,0.03743724],"study_design_scores_gemma":[0.00008451279,0.00001577734,0.6270287,0.00002854974,0.00002824036,0.00001270908,0.0006494996,0.000003090123,0.00001416672,0.004308877,0.3676829,0.0001429347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6738041,0.0003850369,0.00003544387,0.00145955,0.0003600308,0.0002159627,3.066344e-7,0.0001119915,0.3236275],"genre_scores_gemma":[0.9953448,0.0001287584,0.0001848467,0.0003760504,0.0008372749,0.00001240581,0.000002950824,0.00001063787,0.003102251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3466568,"threshold_uncertainty_score":0.9457874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02230966197861129,"score_gpt":0.3338439793868333,"score_spread":0.311534317408222,"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."}}