{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09536242,0.0008495557,0.002242197,0.006911912,0.00118656,0.002324248,0.002023585,0.001410633,0.003379256],"category_scores_gemma":[0.3173577,0.00120906,0.001385615,0.01271779,0.001486223,0.002735117,0.002618432,0.002345048,0.0006183992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036414,"about_ca_system_score_gemma":0.003584837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005022768,"about_ca_topic_score_gemma":0.00326701,"domain_scores_codex":[0.8594682,0.1281432,0.004659405,0.002875628,0.004322039,0.00053154],"domain_scores_gemma":[0.6733654,0.2738991,0.01356516,0.02953791,0.007870846,0.001761552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001075262,0.0003368976,0.225046,0.003621912,0.00566629,0.00136119,0.003247001,0.02333389,0.00144711,0.09737993,0.02359356,0.613891],"study_design_scores_gemma":[0.001063285,0.002044432,0.2096636,0.00326642,0.00249297,0.002380115,0.003122406,0.1797855,0.002355765,0.4749306,0.1183835,0.000511426],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02727071,0.01425904,0.9480913,0.002383641,0.0007098367,0.001174627,0.003161771,0.001285035,0.001664043],"genre_scores_gemma":[0.2255105,0.008219725,0.7534102,0.000776486,0.0007528958,0.005848128,0.004055722,0.0002903313,0.001136035],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09536242,"threshold_uncertainty_score":0.5043307,"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."}}