{"id":"W2204236607","doi":"10.1186/s12874-015-0101-3","title":"Bayesian estimation of associations between identified longitudinal hormone subgroups and age at final menstrual period","year":2015,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Ovarian function and disorders","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Cancer Institute; National Institute on Aging; National Institutes of Health","keywords":"Subgroup analysis; Follicle-stimulating hormone; Medicine; Longitudinal study; Demography; Hormone; Internal medicine; Luteinizing hormone; Meta-analysis","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01745912,0.0001271883,0.0006264502,0.0003792655,0.000159801,0.00001966807,0.0001396064,0.0003761809,0.000643191],"category_scores_gemma":[0.08211054,0.0001103483,0.00008275697,0.0004614308,0.0008947726,0.00007435535,0.0002297637,0.0006170014,0.00005181031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001835601,"about_ca_system_score_gemma":0.001125667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004541125,"about_ca_topic_score_gemma":0.0005611267,"domain_scores_codex":[0.993062,0.003735135,0.000537108,0.0003821221,0.001804204,0.0004794339],"domain_scores_gemma":[0.9909937,0.007241683,0.0001234447,0.0002839344,0.0004078146,0.000949421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004023064,0.0007054191,0.8399003,0.0005142147,0.0005915659,0.0004977531,0.005109882,0.00004154546,0.002805504,0.01353136,0.0404384,0.09184107],"study_design_scores_gemma":[0.00784649,0.001586965,0.9751936,0.0000673757,0.0001610521,0.0001846322,0.002025865,0.004408604,0.0002977285,0.007047419,0.001005657,0.0001745794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7268777,0.0004542943,0.2662682,0.003556469,0.0001860551,0.0003837168,0.00002111377,0.00004179293,0.002210694],"genre_scores_gemma":[0.9299932,0.00005618954,0.06787742,0.00008738138,0.0002369337,0.00002664509,0.0001947085,0.00001820709,0.001509276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2031156,"threshold_uncertainty_score":0.9256212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.547910693898897,"score_gpt":0.5182852696216899,"score_spread":0.02962542427720716,"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."}}