{"id":"W2978236720","doi":"10.3390/app9194103","title":"Overview of Federated Facility to Harmonize, Analyze and Management of Missing Data in Cohorts","year":2019,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Horizon 2020 Framework Programme","keywords":"Missing data; Raw data; Computer science; Data science; Observational study; Harmonization; Sample size determination; Data mining; Statistics","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":[0.00182926,0.00009415561,0.0002141672,0.00005173429,0.00007906003,0.00002174133,0.0003731621,0.00002431447,0.0003938955],"category_scores_gemma":[0.0000137991,0.00008485858,0.000009429053,0.000583737,0.0003309496,0.0001910629,0.0006899291,0.00005592949,0.00007272352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004822629,"about_ca_system_score_gemma":0.00001249151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000600739,"about_ca_topic_score_gemma":0.0001412018,"domain_scores_codex":[0.9983454,0.0000484341,0.0002906794,0.0006514918,0.0004265165,0.0002374843],"domain_scores_gemma":[0.9993804,0.00006213244,0.0001032165,0.0003708067,0.000002405547,0.00008105172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002409158,0.0001418047,0.7822938,0.0003068149,0.00001618392,0.000007329525,0.0006521704,0.0007055962,0.04325409,0.0002917951,0.00007529885,0.172231],"study_design_scores_gemma":[0.0002619403,0.00003645008,0.9899217,0.00008954322,0.00001004461,9.826757e-7,0.0005602838,0.001879369,0.006076745,0.0002977628,0.0007217825,0.0001433627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844421,0.00009476483,0.0004810118,0.0001891219,0.00001672336,0.0005775763,0.00001900414,0.000005485243,0.01417419],"genre_scores_gemma":[0.9962348,0.0001417831,0.003393078,0.0001914763,0.000001225762,0.000006946431,0.000005310525,0.000002580144,0.00002275708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2076279,"threshold_uncertainty_score":0.431288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0755158285083809,"score_gpt":0.3208798524825219,"score_spread":0.245364023974141,"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."}}