{"id":"W2965212561","doi":"","title":"Neural Graph Evolution: Towards Efficient Automatic Robot Design","year":2019,"lang":"en","type":"article","venue":"International Conference on Learning Representations","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Robot; Graph; Artificial intelligence; Artificial neural network; Theoretical computer science; Machine learning","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003845127,0.0002176752,0.000188556,0.0004139147,0.0002301026,0.0005400017,0.001320994,0.00007465209,0.0009237478],"category_scores_gemma":[0.0003987497,0.0002175811,0.0001252372,0.0004819162,0.00006915499,0.00045455,0.0002776266,0.0004975863,0.001347097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001883881,"about_ca_system_score_gemma":0.0001953862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005205979,"about_ca_topic_score_gemma":8.072806e-7,"domain_scores_codex":[0.9973829,0.0002751232,0.0004213848,0.0005807266,0.001008564,0.0003312505],"domain_scores_gemma":[0.9982754,0.0003134531,0.0002816424,0.0005910952,0.0004280072,0.000110391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007209328,0.00003856262,0.002300456,0.000005024675,0.00003980055,0.000006772689,0.0005979454,0.8749052,0.0005706135,0.1186596,0.0001309252,0.002737848],"study_design_scores_gemma":[0.0004183738,0.000186649,0.01787419,0.00005651185,0.00000741267,0.00001944739,0.0002046325,0.9793321,0.0001673986,0.001320499,0.000188142,0.0002245669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01541872,0.000009225609,0.9432251,0.002913251,0.001524917,0.0003785329,0.000001105713,0.0004605167,0.03606866],"genre_scores_gemma":[0.9734409,0.00000574824,0.019472,0.0001407009,0.00006767406,0.00004755506,0.00002111177,0.00001688628,0.006787351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9580222,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05089747332137666,"score_gpt":0.3173870093774977,"score_spread":0.266489536056121,"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."}}