{"id":"W2002119301","doi":"10.1007/s00180-013-0404-y","title":"Efficient iterative computation of mixture weights for pooled order statistics for meta-analysis of multiple type-II right censored data","year":2013,"lang":"en","type":"article","venue":"Computational Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computation; Order statistic; Mathematics; Statistics; Type (biology); Iterative method; Algorithm; Computer science; Applied 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002966835,0.000259133,0.0009582823,0.0002211288,0.0002701739,0.0000408654,0.0003110416,0.0000931465,0.0007921935],"category_scores_gemma":[0.003340285,0.0002220275,0.0001964739,0.0008025665,0.0002006198,0.00006537417,0.00009029225,0.00008026762,0.000009225063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004727364,"about_ca_system_score_gemma":0.0001500249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002418124,"about_ca_topic_score_gemma":0.00002076402,"domain_scores_codex":[0.9975519,0.0001033811,0.001176539,0.0004417605,0.0004933454,0.0002330571],"domain_scores_gemma":[0.9851838,0.008667703,0.0008326867,0.0003914101,0.004809896,0.0001144646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005292699,0.0005054868,0.00001146457,0.0002423436,0.01141392,2.163846e-7,0.0002018002,0.09656163,0.00003496653,0.8588225,0.03177494,0.0003777792],"study_design_scores_gemma":[0.0006228624,0.00007991749,0.0008922314,0.000005739931,0.01867855,4.248723e-7,0.00002321784,0.650143,0.00003783694,0.3292097,0.0001590099,0.0001475862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000732392,0.00004399528,0.8566071,0.0002024937,0.00006342237,0.001516604,0.1407695,0.00003014441,0.00003432774],"genre_scores_gemma":[0.2115035,9.359889e-7,0.7555038,0.00005800675,0.00001845097,0.0002523655,0.03256175,0.00002250271,0.00007871234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5535814,"threshold_uncertainty_score":0.9054019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1239366102069485,"score_gpt":0.3937691969865272,"score_spread":0.2698325867795788,"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."}}