{"id":"W1673729927","doi":"10.1002/jgt.22057","title":"Hermitian Adjacency Matrix of Digraphs and Mixed Graphs","year":2016,"lang":"en","type":"article","venue":"Journal of Graph Theory","topic":"Graph theory and applications","field":"Mathematics","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Javna Agencija za Raziskovalno Dejavnost RS","keywords":"Digraph; Hermitian matrix; Combinatorics; Mathematics; Adjacency matrix; Eigenvalues and eigenvectors; Spectral radius; Matrix (chemical analysis); Interlacing; Arc (geometry); Spectrum (functional analysis); Discrete mathematics; Pure mathematics; Computer science; Graph; Physics","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":[0.0002785778,0.0003414,0.0002788055,0.002064675,0.0006150198,0.001144001,0.0004179085,0.000413079,0.005052464],"category_scores_gemma":[0.001487702,0.0002056142,0.0002080808,0.0009656837,0.001007225,0.001230201,0.0007005578,0.0005360811,0.0005376317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005815246,"about_ca_system_score_gemma":0.0002345545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006752634,"about_ca_topic_score_gemma":0.0006043294,"domain_scores_codex":[0.9996167,0.0001056259,0.00002570741,0.000101364,0.00009546889,0.00005499399],"domain_scores_gemma":[0.999008,0.0003814491,0.0001806468,0.00009988687,0.0001690665,0.0001609681],"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":[0.00002571165,0.0000147539,0.0004049255,0.00004216757,0.000008316307,0.0001183214,0.0001648003,0.002651533,0.00357216,0.981698,0.0009502069,0.01034911],"study_design_scores_gemma":[0.00000920107,0.00002993954,0.0008778266,0.00002009198,0.000007068558,0.0003199236,0.0001384547,0.03420577,0.001676543,0.9565681,0.006126587,0.00002038436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4789514,0.001679856,0.4653997,0.000792808,0.0002807642,0.00007919076,0.0007364525,0.0004068761,0.05167314],"genre_scores_gemma":[0.9585103,0.0003608906,0.03430191,0.000150325,0.0001029625,0.00005833896,0.0002143919,0.00004314077,0.00625773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005052464,"threshold_uncertainty_score":0.01690221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983445087669783,"score_gpt":0.291133383142799,"score_spread":0.2712989322661011,"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."}}