{"id":"W2093639777","doi":"10.1007/s00362-006-0034-3","title":"A note on inference for P(X  <  Y) for right truncated exponentially distributed data","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Inference; Reliability (semiconductor); Monte Carlo method; Confidence interval; Mathematics; Applied mathematics; Statistics; Exponential growth; Maximum likelihood; Statistical inference; Exponential distribution; Algorithm; Computer science; Mathematical analysis; Physics; Artificial intelligence; Quantum mechanics","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":[0.07357881,0.003128121,0.004767888,0.002615153,0.002391342,0.004894134,0.01029512,0.008967146,0.01059887],"category_scores_gemma":[0.2497865,0.002332803,0.005836001,0.00437825,0.00834004,0.01452482,0.00653298,0.023443,0.003706004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003303724,"about_ca_system_score_gemma":0.004335998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01809038,"about_ca_topic_score_gemma":0.01630065,"domain_scores_codex":[0.9653787,0.01978818,0.002747966,0.005177455,0.006317452,0.0005902644],"domain_scores_gemma":[0.6623022,0.2931743,0.002480305,0.03264611,0.008135508,0.001261572],"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":[0.0006290556,0.0002041502,0.005380041,0.001119625,0.001192208,0.002768266,0.001024306,0.037538,0.005268638,0.5718462,0.08508669,0.2879429],"study_design_scores_gemma":[0.0001871655,0.0001813222,0.003483589,0.0004868807,0.0004664903,0.001240083,0.0001356749,0.1715913,0.004870209,0.7587395,0.05832865,0.0002891305],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003193059,0.0009001968,0.9932777,0.002918066,0.001377601,0.00004686897,0.0001747026,0.0002925227,0.00069304],"genre_scores_gemma":[0.01998254,0.002752616,0.9561325,0.005798575,0.006964913,0.0003789053,0.0005214834,0.000534274,0.006934282],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07357881,"threshold_uncertainty_score":0.3891266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.079884625652137,"score_gpt":0.3965803985005759,"score_spread":0.3166957728484389,"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."}}