{"id":"W2072856395","doi":"10.1007/s10463-008-0209-x","title":"A class of multi-sample nonparametric tests for panel count data","year":2008,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Nonparametric statistics; Mathematics; Statistics; Monte Carlo method; Count data; Sample (material); Sample size determination; Data set; Monotonic function; Panel data; Reliability (semiconductor); Statistical hypothesis testing; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00110577,0.0002433389,0.0009562616,0.0001053163,0.0001026036,0.000009085295,0.001205529,0.0001213787,0.00004346709],"category_scores_gemma":[0.06624226,0.0001664228,0.0001394536,0.0004292684,0.001259022,0.0001132354,0.0004040768,0.0001610505,0.000002691005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000123269,"about_ca_system_score_gemma":0.0002191432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001137268,"about_ca_topic_score_gemma":0.00002073572,"domain_scores_codex":[0.9972794,0.00007997618,0.001387737,0.0002950587,0.0006347327,0.0003230703],"domain_scores_gemma":[0.9833241,0.01351511,0.0008760846,0.001434484,0.0007351264,0.0001150808],"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":[0.00005031329,0.001367985,0.000183012,0.00252462,0.0001407655,0.000003172855,0.0003182881,0.00002882701,0.0005354611,0.9858874,0.005429121,0.003531042],"study_design_scores_gemma":[0.0007029249,0.0002957156,0.001314799,0.0004733031,0.0001962761,0.0000196141,0.000071819,0.05483535,0.005156111,0.9356059,0.001079587,0.0002486392],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02276564,0.00006364211,0.9674482,0.0001992012,0.000208076,0.0007123539,0.008182032,0.00001841822,0.0004024495],"genre_scores_gemma":[0.1900382,0.00006291454,0.8097,0.00005811437,0.0000235509,0.00001806593,0.0000279531,0.00002500921,0.00004623236],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1672726,"threshold_uncertainty_score":0.9416232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5826455448929595,"score_gpt":0.4764490893093583,"score_spread":0.1061964555836012,"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."}}