{"id":"W2153622130","doi":"10.1016/j.laa.2009.11.028","title":"The resolvent average for positive semidefinite matrices","year":2009,"lang":"en","type":"article","venue":"Linear Algebra and its Applications","topic":"Mathematical Inequalities and Applications","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Resolvent; Mathematics; Positive-definite matrix; Matrix (chemical analysis); Semidefinite programming; Pure mathematics; Resolvent formalism; Duality (order theory); Applied mathematics; Algebra over a field; Combinatorics; Eigenvalues and eigenvectors; Mathematical optimization","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":[0.0002556623,0.000124384,0.0001506319,0.00002493238,0.0006493023,0.00007778462,0.0001825477,0.00005807098,0.00002025217],"category_scores_gemma":[0.000141726,0.00008492643,0.00007546129,0.0001550811,0.00004903031,0.00005236398,0.00003143482,0.00009146,0.00003145007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001160066,"about_ca_system_score_gemma":0.00001484466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001463444,"about_ca_topic_score_gemma":0.000002049022,"domain_scores_codex":[0.9991142,0.00001934905,0.0003299122,0.0002056941,0.0001174443,0.0002133559],"domain_scores_gemma":[0.9978932,0.001474926,0.0001182194,0.0003109217,0.0001159436,0.0000867539],"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":[0.000005669509,0.00007719419,6.061295e-7,0.0000335899,0.00001308193,6.139967e-8,0.0001612342,9.71903e-7,0.0002176231,0.993017,0.002397862,0.004075075],"study_design_scores_gemma":[0.0001615525,0.00005127048,0.00003380189,0.00001884589,0.00004159316,0.000003689627,0.0001398068,0.003440092,0.0008785378,0.8831602,0.1119464,0.0001241899],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03268045,0.004802075,0.8642535,0.05265911,0.00007619215,0.008712952,0.0008364802,0.0005908568,0.03538841],"genre_scores_gemma":[0.8819534,0.002511286,0.08922285,0.003004394,0.00120793,0.00534211,0.0002000773,0.00009710788,0.01646091],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8492729,"threshold_uncertainty_score":0.4993974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04493906377826337,"score_gpt":0.3394548678274785,"score_spread":0.2945158040492151,"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."}}