{"id":"W4224931240","doi":"10.1109/icassp43922.2022.9746424","title":"Linear-Time Sampling on Signed Graphs Via Gershgorin Disc Perfect Alignment","year":2022,"lang":"en","type":"article","venue":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Simon Fraser University","funders":"","keywords":"Combinatorics; Laplacian matrix; Eigenvalues and eigenvectors; Mathematics; Graph; Discrete mathematics; Pairwise comparison; Algorithm; Physics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007971671,0.0006172658,0.0005307244,0.0005484131,0.001112956,0.0006003486,0.001912603,0.0001336115,0.001104715],"category_scores_gemma":[0.00008716261,0.0006172003,0.0002135392,0.0007627405,0.0002197885,0.0005692867,0.0007682628,0.001427361,0.00006572013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003892877,"about_ca_system_score_gemma":0.0002201174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001976995,"about_ca_topic_score_gemma":0.000002719111,"domain_scores_codex":[0.9944733,0.0002760723,0.0007562323,0.001504132,0.002181305,0.000808988],"domain_scores_gemma":[0.9977376,0.0004857322,0.0005236356,0.0005689027,0.000324089,0.0003600714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001235558,0.001773401,0.0003016175,0.0001277924,0.0003972554,0.001307413,0.001120018,0.09679195,0.4065581,0.02670284,0.006036577,0.4576474],"study_design_scores_gemma":[0.0009967416,0.001392585,0.0001175143,0.0001327064,0.00004468183,0.0001948962,0.0002225151,0.9633512,0.002921367,0.02830089,0.001390144,0.0009347103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0517075,0.0002638126,0.9353846,0.004357977,0.00265721,0.0008507692,0.0002659163,0.0005906541,0.003921575],"genre_scores_gemma":[0.9802346,0.00008219201,0.0157578,0.001563718,0.0004193392,0.0001491099,0.00009533823,0.00006543903,0.00163246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9285271,"threshold_uncertainty_score":0.9998084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0428137008357888,"score_gpt":0.3008793484590243,"score_spread":0.2580656476232355,"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."}}