{"id":"W2154610266","doi":"10.1109/mci.2009.933096","title":"The evolution of swarm grammars- growing trees, crafting art, and bottom-up design","year":2009,"lang":"en","type":"article","venue":"IEEE Computational Intelligence Magazine","topic":"Architecture and Computational Design","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Swarm behaviour; Computer science; Rule-based machine translation; Swarm intelligence; Grammar; Artificial intelligence; Grammar systems theory; Theoretical computer science; Algorithm; Particle swarm optimization","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":[0.0008221317,0.0003400858,0.0002967344,0.0005283827,0.0007492051,0.001588384,0.0007967983,0.000884579,0.001839241],"category_scores_gemma":[0.002282456,0.0003823495,0.0007206906,0.0003725416,0.003037432,0.001829532,0.001173347,0.0009231257,0.0002928938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001269095,"about_ca_system_score_gemma":0.000777705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002756144,"about_ca_topic_score_gemma":0.003213043,"domain_scores_codex":[0.9996616,0.0001156308,0.00002119688,0.00006055532,0.0001096526,0.00003141395],"domain_scores_gemma":[0.9994426,0.0002734342,0.00003814715,0.0001344454,0.00007060084,0.00004068495],"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":[0.00001990874,0.00001703284,0.0005659659,0.0000677599,0.00001918105,0.0001810826,0.0006453873,0.2322281,0.005588097,0.7140974,0.001230429,0.04533979],"study_design_scores_gemma":[0.00001463255,0.00002975813,0.0001810175,0.00003175707,0.00001482116,0.0001171023,0.00008746067,0.438595,0.0040692,0.5412317,0.0156045,0.00002315206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0431347,0.00052577,0.9387768,0.0007720631,0.00006663102,0.00003304347,0.00003667191,0.0004377801,0.0162165],"genre_scores_gemma":[0.5438011,0.0006093492,0.4434822,0.0001781676,0.00002695835,0.00009399193,0.00008904733,0.0002674689,0.01145175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002756144,"threshold_uncertainty_score":0.009208024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684775979717185,"score_gpt":0.2389507181150339,"score_spread":0.2221029583178621,"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."}}