{"id":"W4399567381","doi":"10.1038/s42005-024-01678-7","title":"Neural network approach to quasiparticle dispersions in doped antiferromagnets","year":2024,"lang":"en","type":"article","venue":"Communications Physics","topic":"Physics of Superconductivity and Magnetism","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto; University of Waterloo","funders":"","keywords":"Quasiparticle; Physics; Artificial neural network; Quantum; Ansatz; Hilbert space; Statistical physics; Ground state; Quantum mechanics; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007272165,0.0002757188,0.0004392153,0.0006197642,0.0004484973,0.0007243997,0.0009827286,0.001047465,0.00156363],"category_scores_gemma":[0.00152637,0.0002902253,0.0002770485,0.0003328628,0.001104085,0.0009491633,0.0004893342,0.0007133982,0.0001005835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001129253,"about_ca_system_score_gemma":0.0005514796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006097522,"about_ca_topic_score_gemma":0.006559571,"domain_scores_codex":[0.9998583,0.0000716939,0.000005118377,0.00001275718,0.00002878125,0.00002341075],"domain_scores_gemma":[0.9995074,0.0002954914,0.0000581882,0.0000334929,0.00006496367,0.00004046447],"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":[0.00005599877,0.00004705785,0.0005393602,0.00002737483,0.00001825112,0.00007043689,0.00003955883,0.9593743,0.002337391,0.03541287,0.0001921976,0.001885037],"study_design_scores_gemma":[0.000001552402,0.000002093253,0.00003271353,8.580804e-7,5.128359e-7,0.000001409534,0.000002585235,0.997865,0.00008085997,0.001996701,0.00001452586,0.000001164452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8920988,0.0002642165,0.09534413,0.0009833691,0.00005990797,0.00003400483,0.00009343845,0.0002351818,0.01088701],"genre_scores_gemma":[0.9889848,0.00006025827,0.009226204,0.00004498796,0.00001259208,0.00002646323,0.00002906697,0.00002685811,0.001588656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006097522,"threshold_uncertainty_score":0.01212406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05225273429078119,"score_gpt":0.3018696780696103,"score_spread":0.2496169437788291,"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."}}