{"id":"W2051625332","doi":"10.1007/s00184-012-0381-0","title":"On the goodness-of-fit procedure for normality based on the empirical characteristic function for ranked set sampling data","year":2012,"lang":"en","type":"article","venue":"Metrika","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"RSS; Mathematics; Goodness of fit; Statistics; Context (archaeology); Normality; Data set; Simple random sample; Econometrics; Computer science; Population","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":[0.1033869,0.001839139,0.004883285,0.00646053,0.002553277,0.003969096,0.006154369,0.004371542,0.005854127],"category_scores_gemma":[0.3528737,0.001312248,0.004299496,0.005361257,0.009835822,0.006393075,0.005738933,0.008428429,0.001091063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002314798,"about_ca_system_score_gemma":0.005209679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004774502,"about_ca_topic_score_gemma":0.003186889,"domain_scores_codex":[0.9102542,0.07599085,0.002185318,0.00361742,0.007158712,0.0007935853],"domain_scores_gemma":[0.5333356,0.4317974,0.00410906,0.02107308,0.008487199,0.001197702],"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":[0.0009280396,0.0003987714,0.01268415,0.0007534027,0.0009577965,0.0005787735,0.001496081,0.1649509,0.002184547,0.605059,0.004791564,0.205217],"study_design_scores_gemma":[0.0001821766,0.0005387891,0.004719519,0.0002396706,0.0001616711,0.0004455326,0.0003259032,0.6771927,0.001556688,0.3118012,0.0026748,0.0001612869],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01000207,0.0002090211,0.9884171,0.0002506484,0.00003853128,0.000135049,0.0000879247,0.0002351668,0.0006244855],"genre_scores_gemma":[0.2727518,0.0005431232,0.722145,0.0004574441,0.0002264858,0.001345897,0.0007612099,0.0005480811,0.001220925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1033869,"threshold_uncertainty_score":0.5467689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7426862139722693,"score_gpt":0.5041488291047047,"score_spread":0.2385373848675646,"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."}}