{"id":"W4249884558","doi":"10.32920/ryerson.14645649","title":"On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Evolvability; Representation (politics); Computer science; Rank (graph theory); Genetic programming; Formicoidea; Ant colony; Artificial intelligence; Theoretical computer science; Ant colony optimization algorithms; Mathematical optimization; Mathematics; Biology; Ecology; Evolutionary biology; Aculeata","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":[0.001585847,0.0003882872,0.0003164879,0.0004535146,0.0002665251,0.000586955,0.0007220632,0.0004612549,0.0006299266],"category_scores_gemma":[0.004123644,0.0002767167,0.0003680415,0.0003536371,0.001260232,0.0006378152,0.0008915785,0.0006959059,0.0001074333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003748678,"about_ca_system_score_gemma":0.0004116302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005981424,"about_ca_topic_score_gemma":0.0004158046,"domain_scores_codex":[0.9993507,0.000320352,0.00002165638,0.00008169306,0.0001957843,0.00002978002],"domain_scores_gemma":[0.9986389,0.0009221873,0.0001198851,0.0001391618,0.0001415348,0.00003823385],"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":[0.00007220785,0.00005290019,0.001896029,0.00008317884,0.00004806205,0.0001256945,0.0002627198,0.8242254,0.009560975,0.1002012,0.0002109745,0.06326058],"study_design_scores_gemma":[0.00001092242,0.00008196668,0.0001476336,0.000009057835,0.00001199345,0.00005683603,0.0000112756,0.9809006,0.001383064,0.01666979,0.0007120481,0.000004858289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07240503,0.0001698057,0.9240397,0.0001155538,0.0000140705,0.000035827,0.000006765948,0.0001526062,0.003060664],"genre_scores_gemma":[0.6265648,0.000257744,0.3709791,0.00005357672,0.00001625595,0.0001267839,0.00002327374,0.00006245792,0.001916029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001585847,"threshold_uncertainty_score":0.00838685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06438474259163568,"score_gpt":0.3090230363142603,"score_spread":0.2446382937226246,"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."}}