{"id":"W4400600675","doi":"10.48550/arxiv.2407.07288","title":"Structural Design Through Reinforcement Learning","year":2024,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Structural Engineering and Vibration Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Reinforcement; Reinforcement learning; Computer science; Psychology; Artificial intelligence; Social psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008657417,0.0004192618,0.0003664662,0.0001393586,0.00007591744,0.0001133687,0.0002461293,0.0002626136,0.0003949876],"category_scores_gemma":[0.00003151129,0.0003906531,0.0002274371,0.0002276216,0.00003102676,0.00008275884,0.0002744853,0.001271864,0.0003421854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001849345,"about_ca_system_score_gemma":0.00003174867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005749901,"about_ca_topic_score_gemma":0.000001901372,"domain_scores_codex":[0.9986619,0.00002836773,0.0003931249,0.0003692843,0.0002240413,0.000323281],"domain_scores_gemma":[0.9994137,0.00004104242,0.00005051767,0.0003763816,0.00004009398,0.00007823091],"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":[0.000002383624,4.582723e-7,0.0004390769,0.0002584354,0.0003072073,0.00001035883,0.0004484734,0.9962155,0.0006141224,0.0001855361,0.0005425792,0.0009759332],"study_design_scores_gemma":[0.0001040815,0.00001840917,0.001659278,0.0001534466,0.0001681754,0.000006048064,0.00009341512,0.9892154,0.005873475,0.0008358738,0.001343645,0.0005287922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5890399,0.002382293,0.3988489,0.000128499,0.003108267,0.0002904118,0.00000570542,0.002693989,0.003502037],"genre_scores_gemma":[0.9955812,0.000209299,0.002264857,0.0000367948,0.000357925,0.00003869367,0.00009808297,0.00009570324,0.001317428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4065413,"threshold_uncertainty_score":0.9998546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04625094304070875,"score_gpt":0.258828853248046,"score_spread":0.2125779102073372,"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."}}