{"id":"W2130041384","doi":"10.1093/biomet/93.1.197","title":"Range of correlation matrices for dependent Bernoulli random variables","year":2006,"lang":"en","type":"article","venue":"Biometrika","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bernoulli's principle; Mathematics; Range (aeronautics); Volume (thermodynamics); Statistics; Random variable; Correlation; Econometrics; Combinatorics; Geometry; Engineering","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":[0.01171964,0.001080234,0.001065949,0.002749215,0.001182585,0.003446746,0.00136119,0.001878412,0.004408587],"category_scores_gemma":[0.08460998,0.0007803831,0.001121543,0.001899196,0.00374004,0.004896136,0.003317806,0.002981006,0.001513511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007153715,"about_ca_system_score_gemma":0.000884901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004633914,"about_ca_topic_score_gemma":0.0003365741,"domain_scores_codex":[0.9834694,0.007962808,0.0009643547,0.002941431,0.003868995,0.0007930145],"domain_scores_gemma":[0.9254766,0.0557264,0.008214709,0.004374836,0.004397969,0.001809407],"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":[0.0001157473,0.00005055306,0.003380389,0.00009467162,0.000051911,0.0005655832,0.0004171463,0.01182206,0.002724693,0.9677845,0.0009642876,0.01202848],"study_design_scores_gemma":[0.00004459254,0.00008976638,0.001441563,0.00005785338,0.00001866486,0.001029921,0.0001218937,0.05773906,0.001167052,0.9357885,0.002439241,0.00006198268],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07750799,0.0006521822,0.9068443,0.001253433,0.00005234404,0.0001409491,0.0003569113,0.0001942737,0.01299762],"genre_scores_gemma":[0.757885,0.0009236204,0.2348516,0.0006100472,0.0002759648,0.0008514261,0.0008438694,0.0001297778,0.003628595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01171964,"threshold_uncertainty_score":0.06198013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948474829972553,"score_gpt":0.2992563815711224,"score_spread":0.2697716332713969,"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."}}