{"id":"W2618337801","doi":"10.1103/physics.10.56","title":"Neural Networks Identify Topological Phases","year":2017,"lang":"en","type":"article","venue":"Physics","topic":"Quantum many-body systems","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"D-Wave Systems (Canada)","funders":"U.S. Department of Energy; Kavli Institute for Theoretical Physics, University of California, Santa Barbara; National Science Foundation","keywords":"Artificial neural network; Topology (electrical circuits); Computer science; Phase (matter); Artificial intelligence; Physics; Mathematics; Quantum mechanics","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":[0.0003023553,0.0002898843,0.000237114,0.0007725887,0.0002406328,0.0005710448,0.0004747015,0.0005847313,0.001864337],"category_scores_gemma":[0.002194222,0.0001959499,0.0001984219,0.0002713646,0.0005166967,0.001036361,0.0006535981,0.0006409932,0.0002594124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004021663,"about_ca_system_score_gemma":0.0002554486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054326,"about_ca_topic_score_gemma":0.001296509,"domain_scores_codex":[0.9999093,0.00002322302,0.000003809214,0.00002121795,0.00002195839,0.00002054706],"domain_scores_gemma":[0.9994839,0.0002441073,0.00009698116,0.00005579824,0.00008886956,0.00003030965],"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":[0.0003025106,0.0001463971,0.009115084,0.0002217823,0.00007543695,0.0002025798,0.0002063193,0.6106089,0.03432105,0.1452247,0.00520282,0.1943723],"study_design_scores_gemma":[0.000004223488,0.00001133793,0.0005151608,0.000005562837,0.000003474216,0.00001265791,0.00001060884,0.9727754,0.001764866,0.02455205,0.0003407285,0.000003937193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5754661,0.0008124129,0.4080355,0.001321502,0.0001423629,0.00004980148,0.0002776803,0.001238702,0.01265586],"genre_scores_gemma":[0.9726287,0.0001750456,0.02495874,0.00007752126,0.00003221133,0.00002161645,0.0001815308,0.00003745321,0.0018872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001864337,"threshold_uncertainty_score":0.006236851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04177462495300998,"score_gpt":0.3367711609198534,"score_spread":0.2949965359668434,"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."}}