{"id":"W1972642395","doi":"10.1002/cjs.10119","title":"Comparison of imputation methods for interval censored time‐to‐event data in joint modelling of tree growth and mortality","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; HIV Legal Network","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Forests, Lands and Natural Resource Operations","keywords":"Computer science; Imputation (statistics); Statistics; Censoring (clinical trials); Inference; Event (particle physics); Data mining; Econometrics; Mathematics; Missing data; Artificial intelligence; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.07186103,0.0006882193,0.001771355,0.001852807,0.0007572904,0.002271016,0.004999779,0.002581067,0.002973031],"category_scores_gemma":[0.1971446,0.0008687294,0.003002189,0.002874516,0.001375028,0.003353147,0.003299327,0.003856184,0.000672053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401514,"about_ca_system_score_gemma":0.002190295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004804139,"about_ca_topic_score_gemma":0.003493143,"domain_scores_codex":[0.963214,0.03179332,0.001218438,0.001292994,0.002016662,0.0004645979],"domain_scores_gemma":[0.6611872,0.3059542,0.007206267,0.01571336,0.008558168,0.001380798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002281411,0.0006234069,0.02456469,0.0005718693,0.002279081,0.0002880928,0.001534409,0.4566292,0.0008766693,0.1608889,0.004015432,0.3454469],"study_design_scores_gemma":[0.000156872,0.000174555,0.002701843,0.0001154049,0.0001286925,0.00009174844,0.0001154152,0.9411762,0.0005003272,0.05335133,0.001412468,0.00007497158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01403409,0.0003717798,0.9845063,0.0002781951,0.00005799946,0.000103033,0.00009253413,0.0001837986,0.0003723021],"genre_scores_gemma":[0.2166773,0.0006586661,0.7796218,0.0001989828,0.0001197856,0.0007031282,0.0006228521,0.0002123498,0.001184962],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07186103,"threshold_uncertainty_score":0.380042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4802798748271769,"score_gpt":0.4578115066030907,"score_spread":0.02246836822408621,"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."}}