{"id":"W1990608894","doi":"10.1007/s10463-006-0070-8","title":"Progressive censoring from heterogeneous distributions with applications to robustness","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Mathematics; Robustness (evolution); Order statistic; Exponential distribution; Exponential function; Probability density function; Applied mathematics; Statistics; Exponential family; Econometrics; Mathematical analysis","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":[0.0001313453,0.000203977,0.0003977665,0.00004799465,0.0001913978,0.00002916453,0.0004140511,0.00006711615,0.0001072438],"category_scores_gemma":[0.0008370124,0.0001428024,0.00008881342,0.0004717344,0.0005258278,0.00007328015,0.0001040249,0.0001132174,0.00001500231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002642123,"about_ca_system_score_gemma":0.00007674163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006968224,"about_ca_topic_score_gemma":0.00002810321,"domain_scores_codex":[0.9982287,0.00003236697,0.0007707885,0.0002421287,0.0004756401,0.0002504291],"domain_scores_gemma":[0.9974139,0.0009545913,0.0004281035,0.0006331979,0.0004414818,0.0001286918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001523095,0.0006564463,0.00002833259,0.0001705984,0.00004927974,0.00000261552,0.00003894164,0.001970223,0.00023175,0.9948305,0.001265608,0.0007404056],"study_design_scores_gemma":[0.0003326468,0.00007267803,0.001529438,0.0003205875,0.0001904031,0.00002046014,0.00006139302,0.005238527,0.01817116,0.9716511,0.002117661,0.0002939594],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03572228,0.00001768533,0.9565237,0.0007981416,0.00003758524,0.0008805447,0.005034486,0.00005391893,0.0009316175],"genre_scores_gemma":[0.5999352,0.000001911077,0.399548,0.00002987729,0.00003695043,0.0002262116,0.0001639386,0.00001775398,0.0000401729],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5642129,"threshold_uncertainty_score":0.5823313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08301678619024247,"score_gpt":0.3688059474598679,"score_spread":0.2857891612696254,"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."}}