{"id":"W3185613559","doi":"10.1007/s00366-021-01488-3","title":"Correction to: An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm","year":2021,"lang":"en","type":"article","venue":"Engineering With Computers","topic":"Slime Mold and Myxomycetes Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Slime mold; Chaotic; Computer science; Algorithm; Discipline; Mold; Mathematical optimization; Mathematics; Artificial intelligence; Materials science","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":[0.0001250613,0.0002022345,0.0001899375,0.0002011441,0.00008481722,0.00009209781,0.00007440207,0.00005340995,0.000003260508],"category_scores_gemma":[0.0000300101,0.0002118422,0.00002254777,0.0005508044,0.000008913727,0.0001890059,0.00007364676,0.0001839282,0.000004223281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001978308,"about_ca_system_score_gemma":0.00001963954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001840389,"about_ca_topic_score_gemma":0.000001460307,"domain_scores_codex":[0.998986,0.00004191623,0.0001332369,0.0003209715,0.0001689919,0.0003488649],"domain_scores_gemma":[0.9993812,0.0001138927,0.00001178644,0.0001605959,0.00007738003,0.0002551558],"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":[0.00000944831,0.00002782661,0.0001031554,0.00004646192,0.00004191384,0.00002623942,0.0005774379,0.9731262,0.01106429,0.000001038308,0.00005883507,0.01491716],"study_design_scores_gemma":[0.0003342472,0.0002964967,0.003888431,0.0002635895,0.00001530429,0.0001061691,0.0000247261,0.9904845,0.004292125,3.958077e-7,0.00002040792,0.0002735917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04266351,0.00009816077,0.9552583,0.00002205341,0.001046813,0.0005367512,0.000001973037,0.0003684873,0.000003970952],"genre_scores_gemma":[0.4372371,0.00000393339,0.562539,0.00001204314,0.00009168086,0.00004551904,0.000009667154,0.00004802274,0.00001296855],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3945736,"threshold_uncertainty_score":0.8638675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01816191641357071,"score_gpt":0.241955798165764,"score_spread":0.2237938817521933,"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."}}