{"id":"W2950411888","doi":"10.1002/sta4.143","title":"A matrix variate skew‐<i>t</i> distribution","year":2017,"lang":"en","type":"article","venue":"Stat","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canada Research Chairs","keywords":"Random variate; Matrix (chemical analysis); Skewness; Work (physics); Data Matrix; Multivariate normal distribution; Distribution (mathematics); Maximization","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":[],"consensus_categories":[],"category_scores_codex":[0.0003309887,0.00007998394,0.00009797906,0.0000128567,0.0003550439,0.0003955259,0.0008219081,0.00004042558,0.000008687061],"category_scores_gemma":[0.00005288031,0.00006733335,0.00004626707,0.00003783851,0.00003446143,0.0004443943,0.0002523118,0.00008166514,0.00006245924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001973888,"about_ca_system_score_gemma":0.00003542136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004728754,"about_ca_topic_score_gemma":0.000004635554,"domain_scores_codex":[0.9992902,0.00004732056,0.00009698543,0.000233284,0.0001227955,0.0002093616],"domain_scores_gemma":[0.9988609,0.00002269528,0.0000900451,0.0009121397,0.0000381425,0.00007605252],"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":[0.000002992838,0.00001518885,0.00008460697,0.000005672347,0.000005904755,0.00001757644,0.0001247315,6.653726e-7,0.0004206697,0.8346812,0.004158299,0.1604826],"study_design_scores_gemma":[0.000518608,0.00006189862,0.007248441,0.00002161065,0.00001081784,0.00002190474,0.000001814906,0.02458742,0.002389371,0.8812623,0.08358889,0.0002869296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006016935,0.00005835954,0.9914686,0.001635395,0.0005100982,0.00006973376,0.0000223946,0.00007664434,0.005557058],"genre_scores_gemma":[0.2872172,0.00002564818,0.7106784,0.0001676714,0.0001121876,0.000007667427,0.000007134269,0.000006323324,0.001777811],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2866155,"threshold_uncertainty_score":0.3814065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635138442095585,"score_gpt":0.3195315884150852,"score_spread":0.3031802039941293,"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."}}