{"id":"W2111095022","doi":"10.1109/cec.1999.781955","title":"An evolutionary approach to multiagent heap formation","year":2003,"lang":"en","type":"article","venue":"","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Heap (data structure); Computer science; Cellular automaton; Automaton; Distributed computing; Robot; Mobile robot; Theoretical computer science; Task (project management); Artificial intelligence; Programming language; Engineering","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":[0.0001016012,0.00005158104,0.00004073654,0.00004822158,0.0001100568,0.00006176295,0.0002993995,0.00001917375,0.00001662938],"category_scores_gemma":[0.000005193479,0.00004644024,0.0000202574,0.0002533387,0.000005724747,0.0004849166,0.00003283155,0.00002687521,0.0002482996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002856756,"about_ca_system_score_gemma":0.00001943513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009954616,"about_ca_topic_score_gemma":8.617307e-7,"domain_scores_codex":[0.999454,0.00002886054,0.0000997149,0.0001812536,0.0001169832,0.0001191652],"domain_scores_gemma":[0.9994047,0.000007229209,0.00001530856,0.0004438711,0.00002965888,0.00009917873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[3.299444e-7,0.0002706432,0.00004163645,0.000004217773,0.000001827305,2.544935e-7,0.0005354297,0.001533056,0.005075362,0.9786341,0.005717366,0.008185829],"study_design_scores_gemma":[0.0001219439,0.00002826111,0.002559412,0.000001221089,0.000001494855,0.00002637954,0.00008717666,0.9148369,0.008125951,0.002282012,0.07178579,0.0001434358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003414968,0.00001676797,0.957211,0.0002273391,0.00003378858,0.0001921175,7.230055e-7,0.0001985799,0.03870467],"genre_scores_gemma":[0.5530681,6.13946e-7,0.4463623,0.000270419,0.000007045418,0.00004305174,0.000008721549,0.000001927678,0.0002378804],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.976352,"threshold_uncertainty_score":0.3191472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115046832566303,"score_gpt":0.2485615586318899,"score_spread":0.2274110903062269,"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."}}