{"id":"W4400400027","doi":"10.1016/j.eswa.2024.124710","title":"Survey on Explainable AI: Techniques, challenges and open issues","year":2024,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Computer science; Data science; Artificial intelligence","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":[0.005242317,0.0008660722,0.001462355,0.00497915,0.0007312622,0.004298537,0.003067617,0.001447112,0.01160062],"category_scores_gemma":[0.01473083,0.0007326007,0.00108619,0.008317958,0.00193224,0.009817231,0.00229715,0.00346415,0.002491741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002141541,"about_ca_system_score_gemma":0.002858433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002461597,"about_ca_topic_score_gemma":0.002644201,"domain_scores_codex":[0.997682,0.000684673,0.0002321158,0.0003546743,0.0009232113,0.0001233922],"domain_scores_gemma":[0.9738643,0.02093609,0.0005997535,0.001837491,0.002403573,0.0003587944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006947647,0.0001321005,0.001510257,0.007195679,0.0001340459,0.00008006598,0.0004102765,0.003525367,0.0007007285,0.2577232,0.03279383,0.6957249],"study_design_scores_gemma":[0.00002248652,0.0001237426,0.001971568,0.004791336,0.0001202085,0.0004318132,0.0005110828,0.0121286,0.001227841,0.2704873,0.7081237,0.00006022665],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003558106,0.8175179,0.1269848,0.01688239,0.0009915266,0.0001006969,0.0004435669,0.0005731846,0.03294785],"genre_scores_gemma":[0.03114754,0.8684646,0.08834262,0.002228976,0.002514838,0.0001445407,0.001245015,0.0002128116,0.005698947],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01160062,"threshold_uncertainty_score":0.03880793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07160439259705363,"score_gpt":0.3515282223116297,"score_spread":0.279923829714576,"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."}}