{"id":"W2026408580","doi":"10.1007/bf02829697","title":"Corners of normal matrices","year":2006,"lang":"en","type":"article","venue":"Proceedings of the Indian Academy of Sciences - Section A","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Indian Statistical Institute","keywords":"Diagonal; Normal matrix; Mathematics; Matrix (chemical analysis); Pure mathematics; Geometry; Physics; Materials science; Composite material; Eigenvalues and eigenvectors","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004193282,0.0008478048,0.0006996838,0.002584282,0.0009931357,0.003381808,0.0008990793,0.0008284742,0.01903088],"category_scores_gemma":[0.003162643,0.0004469122,0.0005992642,0.001077714,0.002071344,0.002533823,0.002328683,0.002622844,0.003914742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007910787,"about_ca_system_score_gemma":0.000368868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006395677,"about_ca_topic_score_gemma":0.0006447579,"domain_scores_codex":[0.9994404,0.0001255384,0.00002827084,0.0001207633,0.0001897471,0.00009525926],"domain_scores_gemma":[0.998679,0.0004214229,0.0001875388,0.0001828807,0.0002657812,0.0002634523],"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":[0.0001011376,0.000025042,0.0003085047,0.00003459136,0.000009656686,0.00009984268,0.000247059,0.00133151,0.002682216,0.9752984,0.004664617,0.01519737],"study_design_scores_gemma":[0.00002623884,0.0000476733,0.0002991771,0.00001856916,0.000007565035,0.0002211135,0.0001755768,0.008488047,0.002251115,0.9795792,0.008866215,0.00001949649],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3693935,0.001748058,0.2992088,0.00255009,0.001786674,0.0001544025,0.0007862526,0.0009355248,0.3234367],"genre_scores_gemma":[0.8597952,0.0009287832,0.03686187,0.0005573584,0.0006317524,0.0001352376,0.0007028034,0.0005038052,0.09988327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01903088,"threshold_uncertainty_score":0.06366462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183608720386718,"score_gpt":0.2389479871820609,"score_spread":0.2271118999781937,"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."}}