{"id":"W4226193820","doi":"10.48550/arxiv.2201.01756","title":"Neural network reconstruction of the dense matter equation of state from neutron star observables","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Pulsars and Gravitational Waves Research","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Office of Science; Nvidia; Samson; Nuclear Physics; Bundesministerium für Bildung und Forschung; Xidian University; Walter Greiner Gesellschaft; Deutscher Akademischer Austauschdienst","keywords":"Neutron star; Physics; Equation of state; Polytropic process; RADIUS; Observable; Nuclear matter; Neutron; Astrophysics; Nuclear physics; Quantum mechanics; Nucleon; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005255027,0.000533947,0.0003381469,0.0003863798,0.0002108272,0.0004623082,0.0005846476,0.0007632446,0.0008108801],"category_scores_gemma":[0.002639887,0.0003487942,0.0003479823,0.0003314625,0.0005622191,0.0008083867,0.000551621,0.0009515724,0.0001730922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006710181,"about_ca_system_score_gemma":0.0005948512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008452382,"about_ca_topic_score_gemma":0.007274473,"domain_scores_codex":[0.9998977,0.00002995859,0.000005520566,0.00003139645,0.00001948686,0.00001597212],"domain_scores_gemma":[0.9994891,0.0002479415,0.00009107795,0.00005281492,0.0000823389,0.00003675578],"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":[0.00004878885,0.00002396855,0.003013278,0.00002047487,0.00002325284,0.0000452828,0.00002812156,0.9740381,0.001877791,0.005516767,0.0006308736,0.01473325],"study_design_scores_gemma":[0.000001235095,0.000001350529,0.0001578053,9.528489e-7,6.329341e-7,0.000001741199,0.000001458444,0.9984926,0.0001610512,0.001133493,0.00004646881,0.000001182748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4502958,0.000389026,0.5422778,0.0007706849,0.00008232583,0.00003106659,0.0004735465,0.000990827,0.004688996],"genre_scores_gemma":[0.9495252,0.0001032815,0.04755119,0.00009701234,0.00003239074,0.00003077857,0.0006135179,0.00007449049,0.001971991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008452382,"threshold_uncertainty_score":0.01680636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06093684392692245,"score_gpt":0.2221129277243444,"score_spread":0.161176083797422,"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."}}