{"id":"W2081706679","doi":"10.1109/cec.2012.6256126","title":"Single parent generalization of cellular automata rules","year":2012,"lang":"en","type":"article","venue":"","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Generalization; Cellular automaton; Computer science; Crossover; Automaton; Set (abstract data type); Theoretical computer science; Population; Fidelity; Evolutionary computation; Mobile automaton; Evolutionary algorithm; Mathematics; Automata theory; Artificial intelligence","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":[0.0001023183,0.00005892117,0.00007126326,0.00004176152,0.00004319489,0.00003068246,0.0003406694,0.00002517491,0.0000580839],"category_scores_gemma":[0.000005080513,0.00005143158,0.00003349505,0.000167717,0.00001710219,0.0003028331,0.0001286877,0.00001795401,0.0001258468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000127718,"about_ca_system_score_gemma":0.00001142055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002514469,"about_ca_topic_score_gemma":0.000001440233,"domain_scores_codex":[0.9994271,0.00001915855,0.0001536907,0.0001128841,0.0001380862,0.0001490513],"domain_scores_gemma":[0.9993862,0.00001456996,0.00005585165,0.0004517998,0.00003142692,0.00006017801],"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":[2.61343e-7,0.0003471064,0.001643794,0.00001339643,0.000007201663,2.266228e-7,0.0003293174,0.00003180039,0.2832803,0.6954935,0.002369189,0.01648392],"study_design_scores_gemma":[0.0002181992,0.00003265517,0.008396188,0.000009700656,0.00001257787,0.000006471345,0.00002355724,0.1639869,0.7645244,0.002746022,0.05980248,0.0002407765],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08771437,0.0001819187,0.9060306,0.0001659233,0.0001053429,0.00007204025,0.000002087172,0.0001821723,0.005545534],"genre_scores_gemma":[0.93244,0.000005688759,0.06709494,0.00005009491,0.00004044682,0.000008514267,0.00002422508,0.000004289287,0.000331815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8447256,"threshold_uncertainty_score":0.2097319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03065431270632294,"score_gpt":0.2465405592330757,"score_spread":0.2158862465267527,"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."}}