{"id":"W2071909737","doi":"10.1016/s0167-9473(03)00029-x","title":"Robust estimation under progressive censoring","year":2003,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Statistics; Mathematics; Estimation; Econometrics; Computer science; Economics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004176577,0.0002021407,0.000321319,0.0002097521,0.0003564543,0.0001631411,0.0003206978,0.00006104712,0.001591147],"category_scores_gemma":[0.002412299,0.000207859,0.0000679763,0.001271263,0.0001304741,0.000218704,0.00008846655,0.0001380939,0.000160191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001003502,"about_ca_system_score_gemma":0.0001216027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002099981,"about_ca_topic_score_gemma":0.00002186628,"domain_scores_codex":[0.9978608,0.0001540803,0.0006041731,0.0005411039,0.0005817358,0.0002581443],"domain_scores_gemma":[0.9967158,0.001638031,0.0003086788,0.0007099565,0.0004598338,0.0001676323],"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":[0.000002488769,0.000127696,0.0002417554,0.00001911504,0.0003697845,0.000003540368,0.00001871396,0.1969375,7.525709e-7,0.7929191,0.007979089,0.001380486],"study_design_scores_gemma":[0.0001628495,0.000005698607,0.007897802,0.00000550181,0.0007953696,0.000004056616,0.00002040599,0.5647454,0.000003041472,0.4258475,0.0003659393,0.0001464864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004502778,0.00003050418,0.9897271,0.0001860748,0.00004440763,0.0002198609,0.00859635,0.0001123971,0.0006329865],"genre_scores_gemma":[0.2577082,0.000003619766,0.7242618,0.00008961894,0.00001809052,0.00003185954,0.01776396,0.0000162455,0.0001066633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3678079,"threshold_uncertainty_score":0.9993215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2216471929200212,"score_gpt":0.4167056230781298,"score_spread":0.1950584301581086,"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."}}