{"id":"W1995404757","doi":"10.1111/j.1745-3984.2009.01067.x","title":"The Reliability of Difference Scores in Populations and Samples","year":2009,"lang":"en","type":"article","venue":"Journal of Educational Measurement","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Reliability (semiconductor); Statistics; Population; Variance (accounting); Mathematics; Sample (material); Sample size determination; Standard deviation; Econometrics; Demography; Physics","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":[0.00154343,0.0000524349,0.0001432712,0.00004717665,0.00005328668,0.0000163779,0.00009722285,0.00001743693,0.00002234366],"category_scores_gemma":[0.01056521,0.00003128716,0.00003055247,0.00008002178,0.00005949227,0.00003705541,0.000006693314,0.0000965449,1.417452e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006761886,"about_ca_system_score_gemma":0.0001860575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001585871,"about_ca_topic_score_gemma":0.00003304491,"domain_scores_codex":[0.998835,0.0001357871,0.0004929721,0.0000559013,0.0004055569,0.00007482992],"domain_scores_gemma":[0.9976238,0.001479431,0.0002768584,0.00009726955,0.0004779885,0.00004467433],"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":[0.00003754599,0.0002603862,0.07222807,0.00002733818,0.000007377956,1.642128e-7,0.0002595087,0.000003939411,0.001127246,0.8972977,0.0003406866,0.02841004],"study_design_scores_gemma":[0.00006177272,0.00004658162,0.4811238,0.0000766587,0.000007301063,0.000002677064,0.0000323633,0.00001365543,0.00006204005,0.5185385,0.00001715864,0.00001756016],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.888183,0.0009747212,0.0888762,0.02092907,0.0003707434,0.0002148055,0.000007724353,0.00000194842,0.0004417799],"genre_scores_gemma":[0.789229,0.0000261952,0.2106634,0.00001698978,0.00005529121,0.000001519612,1.057521e-7,0.0000013947,0.000006127712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4088957,"threshold_uncertainty_score":0.9977692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2134094557378299,"score_gpt":0.4190955226912946,"score_spread":0.2056860669534647,"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."}}