{"id":"W4409202067","doi":"10.1016/j.eswa.2025.127553","title":"Feature Similarity Group-Class Activation Mapping (FSG-CAM): Clarity in deep learning models and Enhancement of visual explanations","year":2025,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Shanxi Provincial Key Research and Development Project; National Natural Science Foundation of China","keywords":"CLARITY; Artificial intelligence; Class (philosophy); Similarity (geometry); Feature (linguistics); Computer science; Pattern recognition (psychology); Group (periodic table); Machine learning; Image (mathematics); Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0004003504,0.0001645588,0.0002508905,0.0003315924,0.0003266879,0.0001349844,0.0003799074,0.0001265217,0.000001584029],"category_scores_gemma":[0.00003411774,0.0001599215,0.00002772695,0.001196753,0.00006688277,0.0007171829,0.0001385103,0.0002698384,0.000002883826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001841584,"about_ca_system_score_gemma":0.00008409961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006369571,"about_ca_topic_score_gemma":0.0002550568,"domain_scores_codex":[0.9984797,0.0001284149,0.0003727156,0.000496143,0.0002698938,0.0002531811],"domain_scores_gemma":[0.9988857,0.0002113831,0.000203713,0.0004251033,0.0002118544,0.00006227073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002652161,0.0005720443,0.003411149,0.000251887,0.00007544411,0.000001795322,0.009446902,0.02636257,0.03062606,0.9111086,0.0003262747,0.01779074],"study_design_scores_gemma":[0.0002902792,0.00007660462,0.001344188,0.0003120476,0.000006376054,0.000004137252,0.005683142,0.9653636,0.01363105,0.00405619,0.008935707,0.000296683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01252527,0.0005822473,0.9824904,0.001425664,0.00005412411,0.001045056,0.000001291324,0.00009367698,0.001782321],"genre_scores_gemma":[0.9827515,0.00007029284,0.01527991,0.0001092884,0.00003153677,0.001524096,0.00001754497,0.000008643216,0.0002071285],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9702263,"threshold_uncertainty_score":0.6521409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02718484054903346,"score_gpt":0.2890037241834583,"score_spread":0.2618188836344248,"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."}}