{"id":"W4403674930","doi":"10.1109/tevc.2024.3476443","title":"Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Evolutionary Computation","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Evolutionary computation; Computer science; Artificial intelligence; Computation; Human-based evolutionary computation; Evolutionary algorithm; Intelligent decision support system; Interactive evolutionary computation; Evolutionary programming; Algorithm","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"],"consensus_categories":[],"category_scores_codex":[0.0004643698,0.0003837509,0.0003022757,0.001066749,0.0008593757,0.000676644,0.0003796132,0.0001679525,0.00002393812],"category_scores_gemma":[0.00001583506,0.0004202179,0.0001335219,0.001873701,0.0001159648,0.002017778,0.00001857981,0.0004098106,0.0006254721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191334,"about_ca_system_score_gemma":0.000380251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003989616,"about_ca_topic_score_gemma":0.00003517327,"domain_scores_codex":[0.9966747,0.0002489008,0.0006800764,0.001055548,0.0007564189,0.0005843216],"domain_scores_gemma":[0.9983469,0.000489435,0.00008412296,0.0003577147,0.000406531,0.0003152774],"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":[0.00004783114,0.0001898593,0.000005021294,0.0001212129,0.00006404945,0.0000440879,0.001345345,0.9268045,0.0003154592,0.03557307,0.005915033,0.02957452],"study_design_scores_gemma":[0.0001418447,0.0004717481,0.00009345909,0.0002564549,0.00002852812,0.0001751801,0.0007746816,0.9717089,0.001002043,0.0212409,0.00366301,0.0004432471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002674549,0.001386579,0.9862263,0.004064394,0.003124381,0.0009768932,0.00003378249,0.001004802,0.0005083672],"genre_scores_gemma":[0.9691435,0.00008969829,0.02908348,0.0004421966,0.0001274104,0.0002000306,0.00002347844,0.00004378848,0.000846383],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.966469,"threshold_uncertainty_score":0.9998249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03135290098391107,"score_gpt":0.2893085765388213,"score_spread":0.2579556755549102,"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."}}