{"id":"W4291377769","doi":"10.1016/j.neunet.2022.08.009","title":"Interpretable Artificial Intelligence through Locality Guided Neural Networks","year":2022,"lang":"en","type":"article","venue":"Neural Networks","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Locality; Computer science; Artificial intelligence; Artificial neural network; Deep learning; Convolutional neural network; Layer (electronics); Pattern recognition (psychology); Topology (electrical circuits); Machine learning; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001186636,0.0005610079,0.0005802284,0.0001405195,0.001439534,0.0006685283,0.003760978,0.0001839119,0.0006672144],"category_scores_gemma":[0.00013335,0.0005889162,0.0003394775,0.002323872,0.00028452,0.001621193,0.002922598,0.001708343,0.00005072497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003146218,"about_ca_system_score_gemma":0.00007219821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005655024,"about_ca_topic_score_gemma":0.0001199099,"domain_scores_codex":[0.9939812,0.0007658012,0.001263785,0.001435302,0.0008884289,0.001665463],"domain_scores_gemma":[0.9968486,0.0004968345,0.0003868438,0.001762093,0.0002107758,0.0002948072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005976708,0.0001352977,0.0001384294,0.000004978518,0.00002057486,0.0001945972,0.0005092756,0.8560905,0.00003686141,0.04988823,0.004635017,0.08828644],"study_design_scores_gemma":[0.00005110239,0.0003143692,0.0000326573,0.00001005227,0.00001559766,0.0001319134,0.0003417183,0.9724768,0.0005727243,0.02220332,0.003250916,0.0005987975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01224915,0.0007835171,0.9755979,0.002734571,0.005421854,0.0006265076,0.000005298789,0.0007361032,0.001845129],"genre_scores_gemma":[0.9899675,0.00003845947,0.003338963,0.005340779,0.0007823912,0.0001866374,0.00002325509,0.00005528337,0.0002666796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9777184,"threshold_uncertainty_score":0.9998605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05669420740494637,"score_gpt":0.2999425370425506,"score_spread":0.2432483296376042,"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."}}