{"id":"W2007493872","doi":"10.1002/sim.2737","title":"Biased odds ratios from dichotomization of age","year":2006,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; Columbia College","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health","keywords":"Odds; Odds ratio; Statistics; Demography; Medicine; Econometrics; Computer science; Logistic regression; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.08406337,0.001136472,0.002519076,0.002759406,0.0007720811,0.003318683,0.002534899,0.002601284,0.003447652],"category_scores_gemma":[0.4455324,0.0007481024,0.002067998,0.002690674,0.00634592,0.005810868,0.003558496,0.004462754,0.0006670817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001681373,"about_ca_system_score_gemma":0.001267857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001436657,"about_ca_topic_score_gemma":0.0009211514,"domain_scores_codex":[0.903351,0.08016694,0.002715092,0.005729166,0.006941798,0.001095978],"domain_scores_gemma":[0.5620477,0.3888797,0.02051454,0.02233095,0.005362125,0.0008649009],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004550692,0.0001713406,0.1777812,0.002009297,0.003040799,0.002074714,0.004361209,0.03738206,0.002337336,0.4777188,0.01199307,0.2765796],"study_design_scores_gemma":[0.0003385729,0.000300646,0.03112566,0.0006886202,0.0007790367,0.002416218,0.0007053548,0.07047093,0.00276071,0.8825906,0.007678115,0.0001455923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.134953,0.01127785,0.8284968,0.01178915,0.0007995826,0.0005140617,0.0009276966,0.0005678055,0.01067402],"genre_scores_gemma":[0.8321137,0.002620477,0.1567855,0.005002762,0.0006423759,0.0007351584,0.0005451214,0.0001867516,0.001368205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9159366,"threshold_uncertainty_score":0.444575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05253306517601675,"score_gpt":0.3872355764733088,"score_spread":0.3347025112972921,"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."}}