{"id":"W2042654193","doi":"10.1016/j.jspi.2010.07.005","title":"A Jonckheere–Terpstra-type test for perfect ranking in balanced ranked set sampling","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Ranking (information retrieval); Nonparametric statistics; Statistics; RSS; Statistic; Test statistic; Sampling (signal processing); Type I and type II errors; Type (biology); Test (biology); Set (abstract data type); Statistical hypothesis testing; Algorithm; Artificial intelligence; Computer science","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":[0.0005494643,0.0001145066,0.0002930029,0.00007990912,0.0001019109,0.00007505699,0.0001007705,0.00007570988,0.00009847159],"category_scores_gemma":[0.01323934,0.00009627258,0.00002911168,0.0001258601,0.0000983734,0.00009899266,0.00001464043,0.0004229336,0.000002598681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001872751,"about_ca_system_score_gemma":0.00008071251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003612536,"about_ca_topic_score_gemma":0.000003773204,"domain_scores_codex":[0.9989272,0.00002626544,0.0005560663,0.0001267846,0.0001700052,0.0001936544],"domain_scores_gemma":[0.9916888,0.007630634,0.0002158308,0.00008228825,0.0002504046,0.0001319713],"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":[0.0002079024,0.0002054349,0.01911461,0.0002109458,0.00003300629,0.00001941419,0.0006143709,0.00008105573,0.0110682,0.9578018,0.001983566,0.008659678],"study_design_scores_gemma":[0.003416912,0.0006495969,0.2089647,0.0006291782,0.0001242819,0.000175695,0.0003314147,0.08168995,0.0004056362,0.7019167,0.001246695,0.0004492405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1564262,0.00001624773,0.8426952,0.0001647235,0.0001002636,0.0001250209,0.00026734,0.00001358696,0.0001914188],"genre_scores_gemma":[0.8325961,0.000004381349,0.1672443,0.00005300512,0.0000551702,0.000006826194,0.00002560069,0.000007403059,0.000007229548],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6761699,"threshold_uncertainty_score":0.9950725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1232962016839542,"score_gpt":0.4428703394002491,"score_spread":0.3195741377162948,"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."}}