{"id":"W1899528446","doi":"10.1007/978-0-8176-4807-7_12","title":"Maximum Likelihood Estimation in Progressive Type-II Censoring","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Weibull distribution; Inference; Mathematics; Maximum likelihood; Statistics; Pareto distribution; Order statistic; Laplace distribution; Laplace transform; Applied mathematics; Exponential distribution; Econometrics; Computer science; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002712684,0.001089286,0.001178029,0.0007000547,0.0003063479,0.001421296,0.001669183,0.001433332,0.009442317],"category_scores_gemma":[0.01266512,0.0009705631,0.0009283083,0.001591686,0.001337455,0.002409333,0.001633051,0.002955415,0.005115673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006765634,"about_ca_system_score_gemma":0.0006382436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008044668,"about_ca_topic_score_gemma":0.0009532042,"domain_scores_codex":[0.9988418,0.0005672915,0.00005744284,0.0001661923,0.0003277097,0.00003964004],"domain_scores_gemma":[0.9963441,0.002889046,0.0001095531,0.0003856759,0.0002371367,0.00003440827],"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":[0.00003491386,0.00003717794,0.000460257,0.0003941881,0.00006498465,0.0001625409,0.0001670002,0.04816461,0.001106319,0.640987,0.02689857,0.2815224],"study_design_scores_gemma":[0.00001033556,0.00001483219,0.0003775928,0.0001396338,0.00002366597,0.0002191106,0.00002428716,0.1462954,0.0009885081,0.8175089,0.03436711,0.00003063788],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004847729,0.002230495,0.9887407,0.000342374,0.0001373188,0.000009827414,0.00007458866,0.0001688001,0.007811097],"genre_scores_gemma":[0.08284867,0.01454452,0.8161885,0.0008089548,0.001710206,0.0002900399,0.001092969,0.001019195,0.08149699],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009442317,"threshold_uncertainty_score":0.03158772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05293076700862998,"score_gpt":0.3427044919164921,"score_spread":0.2897737249078621,"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."}}