{"id":"W1969978468","doi":"10.1016/j.jfa.2008.12.022","title":"Multi-variable subordination distributions for free additive convolution","year":2009,"lang":"en","type":"article","venue":"Journal of Functional Analysis","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Subordination (linguistics); Convolution (computer science); Infinite divisibility; Connection (principal bundle); Pure mathematics; Joint probability distribution; Free probability; Space (punctuation); Operator (biology); Brownian motion; Distribution (mathematics); Variable (mathematics); Integer (computer science); Convolution power; Discrete mathematics; Mathematical analysis; Geometry; Fourier transform","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":[],"consensus_categories":[],"category_scores_codex":[0.0004992171,0.00009127354,0.0002931122,0.000296282,0.0002188636,0.00003763921,0.0001262575,0.00005845417,0.0001940936],"category_scores_gemma":[0.000755876,0.0000747114,0.0004748612,0.0009708747,0.00002040093,0.0002188502,0.000008323748,0.0001034524,0.000003198452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225359,"about_ca_system_score_gemma":0.00006781812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000671878,"about_ca_topic_score_gemma":0.000009599154,"domain_scores_codex":[0.9989669,0.00003165925,0.0005015212,0.0001098395,0.0002692929,0.0001207825],"domain_scores_gemma":[0.9976362,0.000479522,0.000580702,0.000151642,0.001082444,0.00006947565],"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":[0.0006964807,0.002334774,0.001312166,0.00003524821,0.005236603,0.000002767986,0.0001453405,0.009884895,0.008203987,0.7987767,0.1693741,0.003996908],"study_design_scores_gemma":[0.007716551,0.0004897349,0.09588971,0.00003461187,0.0130875,0.00004435458,0.0003165061,0.08641504,0.0009462503,0.754753,0.03987636,0.0004303981],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008411448,0.00009910123,0.9889843,0.00165231,0.00008437929,0.0001382661,0.0003748812,0.00001483651,0.0002404857],"genre_scores_gemma":[0.8656452,0.00003481441,0.1322722,0.00008526703,0.0005143824,0.00002634476,0.0002856419,0.000007245923,0.001128939],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8572337,"threshold_uncertainty_score":0.3046643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03605950238897156,"score_gpt":0.3111286753288073,"score_spread":0.2750691729398357,"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."}}