{"id":"W2031305766","doi":"10.1002/gepi.10280","title":"Longitudinal data analysis in pedigree studies","year":2003,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"National Institute of Environmental Health Sciences","keywords":"Statistic; Trait; Statistics; Framingham Heart Study; Biology; Summary statistics; Longitudinal study; Longitudinal data; Genetic model; Type I and type II errors; Genetics; Mathematics; Computer science; Gene; Framingham Risk Score; Data mining; Medicine","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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004174937,0.0002662668,0.0009017863,0.0002294693,0.00009328457,0.000004056929,0.0005828388,0.0003664955,0.0000713507],"category_scores_gemma":[0.01273375,0.0002460379,0.0001732721,0.0005459,0.0002322397,0.000003483435,0.000358771,0.0001860349,0.00003743837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004282334,"about_ca_system_score_gemma":0.0001109466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001272228,"about_ca_topic_score_gemma":0.00239717,"domain_scores_codex":[0.9952745,0.001789239,0.0009492046,0.001152972,0.00008059065,0.0007535355],"domain_scores_gemma":[0.9972016,0.0006340322,0.0002942441,0.001633367,0.0001064778,0.0001302298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001190601,0.00004554471,0.9861634,0.000007923977,0.0007821709,0.000005808408,0.00003178489,0.005390945,0.0002951085,0.0005300316,0.005515045,0.001220318],"study_design_scores_gemma":[0.0004563384,0.0001659603,0.974861,0.000004123823,0.0003265109,0.00003154414,0.0001792094,0.001190704,0.00005557932,0.006374998,0.01604743,0.0003065696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9302464,0.02382111,0.04314961,0.0009288291,0.0004064534,0.000231194,0.00004761994,0.00001599668,0.001152768],"genre_scores_gemma":[0.9292871,0.003969116,0.06465551,0.0009985655,0.0001995312,0.0000451211,0.0003468182,0.00002051265,0.0004776682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0215059,"threshold_uncertainty_score":0.9999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1477883566750051,"score_gpt":0.3971166252266567,"score_spread":0.2493282685516516,"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."}}