{"id":"W4394793009","doi":"10.61091/um119-07","title":"The Index Weighted Hermitian Adjacency Matrices for Mixed Graphs","year":2024,"lang":"en","type":"article","venue":"Utilitas Mathematica","topic":"Graph theory and applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Spectral radius; Mathematics; Hermitian matrix; Adjacency list; Adjacency matrix; Combinatorics; Two-graph; Chordal graph; Indifference graph; Eigenvalues and eigenvectors; Discrete mathematics; Graph; Pure mathematics; Line graph; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003983277,0.0005762735,0.0003904079,0.002020802,0.0005827228,0.001173609,0.0007483924,0.0006345136,0.002512026],"category_scores_gemma":[0.002203347,0.0002338744,0.0002700288,0.001066041,0.001099437,0.002000337,0.00078853,0.0009499649,0.0003895764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003867913,"about_ca_system_score_gemma":0.0001595481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001839627,"about_ca_topic_score_gemma":0.0002186026,"domain_scores_codex":[0.9995613,0.0001238669,0.0000211132,0.0001073392,0.0001343024,0.00005218308],"domain_scores_gemma":[0.9987105,0.0004585353,0.0003376619,0.0001291838,0.0002144855,0.0001496012],"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":[0.00005172873,0.0000229017,0.0006787734,0.00006993226,0.00001648356,0.0001132628,0.0001486323,0.008209244,0.01165632,0.9650773,0.000905744,0.01304979],"study_design_scores_gemma":[0.000009573049,0.00005686404,0.001152823,0.00001640676,0.00001245436,0.0004694274,0.00009469992,0.09917005,0.004362193,0.8913441,0.003277439,0.00003398721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3123059,0.0007310424,0.6619322,0.000321676,0.0001148208,0.00007063232,0.0003767522,0.0002405507,0.02390635],"genre_scores_gemma":[0.923007,0.0004184854,0.07197688,0.000163072,0.0001769841,0.0001010271,0.0002399231,0.00007362881,0.003843041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002512026,"threshold_uncertainty_score":0.008403599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02996141415429701,"score_gpt":0.3175685700551442,"score_spread":0.2876071559008471,"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."}}