{"id":"W3174204509","doi":"10.1609/aaai.v35i18.17873","title":"Logic Guided Genetic Algorithms (Student Abstract)","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo; University of Toronto","funders":"","keywords":"Conjunction (astronomy); Computer science; A priori and a posteriori; Set (abstract data type); Algorithm; Genetic algorithm; Function (biology); Fraction (chemistry); Symbolic regression; Data set; State (computer science); Artificial intelligence; Machine learning; Genetic programming; Programming language","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":[0.0006503672,0.0002526453,0.0003225854,0.0001478933,0.0002273542,0.0005847248,0.002939021,0.0001061157,0.0005703644],"category_scores_gemma":[0.001095106,0.0001968233,0.000151615,0.001220921,0.0002554827,0.0002959721,0.0009623287,0.0003846207,0.0003069057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007066318,"about_ca_system_score_gemma":0.0003243401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002035981,"about_ca_topic_score_gemma":0.000003404655,"domain_scores_codex":[0.9967118,0.00003646608,0.0008154364,0.0007402569,0.001216366,0.0004796836],"domain_scores_gemma":[0.9964736,0.0001431075,0.0003710147,0.0005984921,0.002241425,0.0001724123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001083593,0.0004228841,0.0001787803,0.00005145954,0.00003700983,0.00001476606,0.0007403513,0.0009447922,0.02065386,0.8545587,0.0007199689,0.1216666],"study_design_scores_gemma":[0.0000636901,0.0001359902,0.002235179,0.0001482258,0.00001700008,0.00004543909,0.0004461119,0.2976792,0.5362161,0.162263,0.0003567815,0.0003932489],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04365429,0.000273324,0.8440613,0.02098462,0.002402207,0.001400504,0.00001743449,0.000367215,0.08683907],"genre_scores_gemma":[0.8579805,0.0002146154,0.1393615,0.0005211419,0.0001279407,0.0000446739,0.000001096188,0.00002157739,0.001726928],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8143262,"threshold_uncertainty_score":0.8026223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1401159445751239,"score_gpt":0.3638528095070106,"score_spread":0.2237368649318867,"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."}}