{"id":"W2007401066","doi":"10.5705/ss.2011.197","title":"Semiparametric accelerated failure time model for length-biased data with application to dementia study","year":2013,"lang":"en","type":"article","venue":"Statistica Sinica","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Censoring (clinical trials); Estimator; Statistics; Econometrics; Estimating equations; Survival analysis; Computer science; Accelerated failure time model; Maximum likelihood; Population; Dementia; Mathematics; Medicine; Internal medicine; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02835899,0.001176263,0.00257823,0.002317198,0.0006424491,0.001847287,0.003705502,0.001840368,0.003108445],"category_scores_gemma":[0.07518317,0.0007016078,0.002517389,0.00197699,0.001958119,0.001946539,0.002463782,0.002817138,0.0004242111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001360713,"about_ca_system_score_gemma":0.002473761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007764863,"about_ca_topic_score_gemma":0.003892979,"domain_scores_codex":[0.9914545,0.006416973,0.0003395082,0.000662629,0.0007742443,0.0003521194],"domain_scores_gemma":[0.9270513,0.06017278,0.004957209,0.00368721,0.003398308,0.000733277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003654436,0.0001754147,0.0266927,0.0006396229,0.0007869266,0.001191279,0.001214724,0.4922013,0.00198818,0.4034486,0.003266255,0.06802965],"study_design_scores_gemma":[0.00008616172,0.0001593835,0.002915321,0.00006611914,0.0001435216,0.0002707451,0.00008159946,0.9036185,0.0002755424,0.09076952,0.00156404,0.0000496491],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02254541,0.0006690713,0.9754131,0.0004894766,0.00005986829,0.000112587,0.0001693563,0.0001222995,0.000418902],"genre_scores_gemma":[0.6660733,0.002297146,0.3223145,0.0005132917,0.0003538643,0.001694958,0.001009233,0.000134448,0.005609121],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02835899,"threshold_uncertainty_score":0.1499784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.176979394857652,"score_gpt":0.4207345544160272,"score_spread":0.2437551595583752,"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."}}