{"id":"W4391341529","doi":"10.1109/tevc.2024.3354471","title":"IEEE Computational Intelligence Society Information","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Evolutionary Computation","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Gottfried Wilhelm Leibniz Universität Hannover; Universiteit Maastricht; Ulster University; Victoria University of Wellington; Leibniz-Gemeinschaft; St. Francis Xavier University; Manchester Metropolitan University; Victoria University; Queen Mary University of London; Hainan University; University of Missouri","keywords":"Computer science; Computational intelligence; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002694472,0.0001506419,0.0001739991,0.0003228529,0.0003355177,0.0001706314,0.0001108657,0.00007806777,0.00119683],"category_scores_gemma":[0.000003630284,0.0001831356,0.0002170012,0.0004292807,0.0001125913,0.00123405,0.000002008202,0.0001752115,0.02151386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285356,"about_ca_system_score_gemma":0.00005087093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000416802,"about_ca_topic_score_gemma":0.000001378035,"domain_scores_codex":[0.9988242,0.00001107617,0.0005406633,0.0003423651,0.00008244238,0.0001991995],"domain_scores_gemma":[0.9995512,0.0001154462,0.0001028403,0.0001069312,0.00006623792,0.00005730454],"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":[0.00001095633,0.00006357544,0.0000112054,0.00003955324,0.0001080799,7.777327e-7,0.001129617,0.8993403,0.000001233792,0.02657619,0.06282599,0.009892515],"study_design_scores_gemma":[0.000141907,0.00004696659,0.0002649681,0.00002956526,0.00001078385,0.000009338168,0.0003116983,0.9376842,0.00002702223,0.03129571,0.02995828,0.0002194948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00113584,0.0003229965,0.9764413,0.0004090217,0.005908682,0.000183777,0.0006534896,0.000232224,0.01471272],"genre_scores_gemma":[0.9860876,0.0001019271,0.00741193,0.0002849926,0.00008572177,0.00003710185,0.00006641643,0.00001340072,0.005910863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9849518,"threshold_uncertainty_score":0.9997162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303743655357333,"score_gpt":0.2277543577714705,"score_spread":0.1947169212178971,"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."}}