{"id":"W4210761584","doi":"10.1002/9781118521373.wbeaa135","title":"Harmonization","year":2015,"lang":"en","type":"other","venue":"The Encyclopedia of Adulthood and Aging","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Victoria","funders":"National Institute for International Education; National Institute on Aging; National Institutes of Health","keywords":"Harmonization; Matching (statistics); Computer science; Process (computing); Data science; Process management; Business; Statistics; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004381264,0.000191515,0.0002038963,0.00004606481,0.00007012196,0.00000951026,0.0001906196,0.0000966675,0.001614594],"category_scores_gemma":[0.00007446585,0.0001402379,0.00002390674,0.0001414657,0.0001968378,0.00006559646,0.0002145591,0.000204626,0.000243905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004404898,"about_ca_system_score_gemma":0.0000198235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004436721,"about_ca_topic_score_gemma":0.0000904667,"domain_scores_codex":[0.9988017,0.0001137632,0.0001946974,0.0003490995,0.0003025466,0.0002382052],"domain_scores_gemma":[0.9993291,0.00004754866,0.0002181809,0.0002918087,0.000004514055,0.0001088269],"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":[0.000008656222,0.00008560724,0.01699595,0.0001808309,0.00004783142,0.00001250257,0.005946375,0.00005138062,0.000215452,0.00006035725,0.8019912,0.1744038],"study_design_scores_gemma":[0.0002580738,0.00002586333,0.003690052,0.0001921347,0.00004468314,0.000004871544,0.0004097191,0.00008136137,0.00004106606,0.000286422,0.9947399,0.0002257898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002942225,0.001021598,0.000414278,0.0005292344,0.0001660481,0.0004082399,0.0000306353,0.00006734526,0.9944204],"genre_scores_gemma":[0.04670467,0.01915659,0.003822736,0.001295302,0.001065281,0.00005388349,0.0001179143,0.0007141235,0.9270695],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1927488,"threshold_uncertainty_score":0.999298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008838345465407918,"score_gpt":0.2328009885907758,"score_spread":0.2239626431253679,"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."}}