{"id":"W4414270260","doi":"10.1109/tkde.2025.3611170","title":"A Multi-Objective Explanation Framework for Graph Neural Networks","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Focus (optics); Graph; Artificial neural network; Attribution; Graph theory; Data modeling; Pareto principle","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001732201,0.001178686,0.0005762813,0.001457536,0.0004688695,0.001079497,0.001529326,0.00109122,0.003246161],"category_scores_gemma":[0.004623385,0.000331735,0.001163292,0.001050484,0.0007487276,0.001641403,0.001404456,0.001474559,0.0002351959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001547258,"about_ca_system_score_gemma":0.001197817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006697935,"about_ca_topic_score_gemma":0.008810559,"domain_scores_codex":[0.9990845,0.0004663377,0.00004745498,0.0001808484,0.0001590188,0.00006187721],"domain_scores_gemma":[0.9982692,0.001144347,0.0001950068,0.00009907545,0.0002323525,0.00006000119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000390833,0.0000566279,0.001690788,0.0001853046,0.0001250471,0.0001517142,0.0002201485,0.7993025,0.0008648199,0.1139755,0.001655881,0.08173268],"study_design_scores_gemma":[0.000008256688,0.00002222926,0.0002258181,0.00002303889,0.00002059774,0.00001858554,0.00001872349,0.9436304,0.0002034772,0.05485043,0.0009703196,0.000008118338],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007868742,0.0004010102,0.9890305,0.0004489014,0.00002414744,0.00006141052,0.0001502107,0.0002362567,0.001778787],"genre_scores_gemma":[0.4958695,0.0008137629,0.4974721,0.0002730755,0.0001067484,0.0004918156,0.0006836096,0.0001335548,0.004155765],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006697935,"threshold_uncertainty_score":0.01331788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03820802667668711,"score_gpt":0.310864001282105,"score_spread":0.2726559746054179,"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."}}