{"id":"W1966359789","doi":"10.1037/1082-989x.12.4.399","title":"Toward using confidence intervals to compare correlations.","year":2007,"lang":"en","type":"article","venue":"Psychological Methods","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":758,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confidence interval; Statistics; Robust confidence intervals; Mathematics; Sample size determination; Dependency (UML); Correlation; Nominal level; Sampling (signal processing); Confidence distribution; Sample (material); Econometrics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.020981,0.0002963858,0.0009653323,0.0001466595,0.0001132431,0.00005713073,0.0006240472,0.000228412,0.001776686],"category_scores_gemma":[0.2010913,0.0002316169,0.00024217,0.0006947675,0.00027161,0.0000603097,0.0002224239,0.0006152294,0.0001710537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008430584,"about_ca_system_score_gemma":0.00001257553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009550187,"about_ca_topic_score_gemma":0.000001708654,"domain_scores_codex":[0.9934767,0.003096048,0.001614716,0.0007637758,0.0004125689,0.000636223],"domain_scores_gemma":[0.9027226,0.09551849,0.0003194914,0.0007088883,0.0002298955,0.000500637],"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":[0.0006887632,0.0008721092,0.001881923,0.00008779249,0.0001027283,0.0001020892,0.0006326517,0.00002360665,0.01061919,0.6164291,0.004276105,0.3642839],"study_design_scores_gemma":[0.0005004468,0.0002307715,0.01009108,0.0001076506,0.00007127367,0.00004729715,0.0001480489,0.0004133864,0.002427461,0.9839951,0.00162304,0.0003444463],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0253276,0.00004020152,0.9607531,0.0005206976,0.002222108,0.0006684487,0.00001751149,0.0002341467,0.01021612],"genre_scores_gemma":[0.1170871,0.000003497593,0.8805161,0.001873572,0.0003502162,0.00002039245,4.965482e-7,0.00003088066,0.00011783],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.367566,"threshold_uncertainty_score":0.9991359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.915936087266207,"score_gpt":0.7443180110581955,"score_spread":0.1716180762080115,"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."}}