{"id":"W4403818860","doi":"10.48550/arxiv.2410.00247","title":"Inferring three-nucleon couplings from multi-messenger neutron-star observations","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Workforce Development for Teachers and Scientists; Los Alamos National Laboratory; National Nuclear Security Administration; Office of Science; Gauss Centre for Supercomputing; Deutsche Forschungsgemeinschaft; Government of Canada; Ministry of Colleges and Universities; Nuclear Physics; Natural Sciences and Engineering Research Council of Canada; Institut Périmètre de physique théorique; Advanced Scientific Computing Research; U.S. Department of Energy; European Commission; Technische Universität Darmstadt; Bundesministerium für Bildung und Forschung; University of Washington; National Science Foundation; National Energy Research Scientific Computing Center","keywords":"Neutron star; Physics; Nucleon; Star (game theory); Nuclear physics; Astrophysics; Neutron; Particle physics; Astronomy","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":[0.0009739579,0.00031225,0.0003130196,0.001131885,0.0004625355,0.0006302648,0.0004263333,0.0005048205,0.000832582],"category_scores_gemma":[0.002710083,0.0001999482,0.0002578436,0.000519314,0.0005475067,0.001010712,0.001032323,0.0007032329,0.0001561102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004864017,"about_ca_system_score_gemma":0.0002659431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001950217,"about_ca_topic_score_gemma":0.002773613,"domain_scores_codex":[0.9998152,0.00005313006,0.000007270552,0.00004832318,0.00005375988,0.00002238676],"domain_scores_gemma":[0.9992392,0.0002867295,0.0002208841,0.0001302618,0.00003804003,0.00008492773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005334122,0.0002690501,0.3626767,0.0003728789,0.0005154781,0.001243015,0.001187874,0.0819026,0.1628922,0.3282036,0.002413569,0.0577896],"study_design_scores_gemma":[0.00007363981,0.00007390561,0.2265921,0.00008938138,0.0000997535,0.0004620956,0.0004417419,0.4230663,0.03630137,0.3029338,0.009765928,0.00009987201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9308663,0.0004707544,0.05741211,0.0003137802,0.00003848952,0.00001637397,0.0006560213,0.0002753085,0.009950843],"genre_scores_gemma":[0.9928569,0.0001436046,0.00644597,0.0000406726,0.0000175626,0.000004964454,0.000296574,0.00002378501,0.0001700598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001950217,"threshold_uncertainty_score":0.005150855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1349962663994839,"score_gpt":0.2307301420163642,"score_spread":0.09573387561688032,"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."}}