{"id":"W2504494579","doi":"10.1145/2908812.2908887","title":"Discovering Rubik's Cube Subgroups using Coevolutionary GP","year":2016,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reuse; Task (project management); Computer science; Genetic programming; Reinforcement learning; Cube (algebra); Population; Decomposition; Process (computing); Genetic algorithm; Sequence (biology); Theoretical computer science; Artificial intelligence; Machine learning; Mathematics; Programming language; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000796589,0.00009834475,0.00008159706,0.00005625155,0.0002338051,0.00004763235,0.0004948777,0.00003530686,0.00007568518],"category_scores_gemma":[0.000009601542,0.0000661779,0.00005355048,0.0002718181,0.00006004201,0.0009710053,0.0002833625,0.00004181117,0.000162881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009833481,"about_ca_system_score_gemma":0.000066097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000693352,"about_ca_topic_score_gemma":0.000005767472,"domain_scores_codex":[0.9990749,0.00001875734,0.000161996,0.0003171951,0.000185586,0.0002415269],"domain_scores_gemma":[0.9993014,0.00007166879,0.00004357354,0.0004494472,0.00004907405,0.00008488201],"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":[0.000001557079,0.00009117107,0.002563833,0.000003445183,0.00001174097,0.000004565496,0.00005747009,0.0002699523,0.02769305,0.9551926,0.001981764,0.01212888],"study_design_scores_gemma":[0.001251894,0.0001083185,0.1163912,0.0001232911,0.00001710649,0.000308332,0.00009730056,0.6952281,0.005629475,0.1176061,0.06207763,0.001161237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03988577,0.00009024651,0.9543304,0.002515611,0.000157835,0.00008600021,0.000005871006,0.0002040341,0.002724207],"genre_scores_gemma":[0.8107913,0.0000224014,0.1871119,0.0001412923,0.0001384039,0.00001659135,0.000001458127,0.000007367669,0.001769299],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8375864,"threshold_uncertainty_score":0.2698657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973406502928331,"score_gpt":0.2488907133229868,"score_spread":0.2291566482937035,"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."}}