{"id":"W2921493897","doi":"10.1103/physrevc.101.044904","title":"Exploring the influence of bulk viscosity of QCD on dilepton tomography","year":2020,"lang":"en","type":"article","venue":"Physical review. C","topic":"High-Energy Particle Collisions Research","field":"Physics and Astronomy","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Office of Energy Research and Development; Nuclear Physics; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canada Foundation for Innovation; U.S. Department of Energy; National Science Foundation","keywords":"Physics; Large Hadron Collider; Particle physics; Volume viscosity; Quark–gluon plasma; Hadron; Viscosity; Plasma; Quantum chromodynamics; Nuclear physics; Relativistic Heavy Ion Collider; QCD matter; Heavy ion; Ion; Thermodynamics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001277951,0.0001081616,0.0003174967,0.00001957512,0.00005660705,0.000008356431,0.0003433126,0.000005424425,0.00003283251],"category_scores_gemma":[0.00007986771,0.00006895478,0.0002209232,0.0006897761,0.0001114942,0.0001279161,0.0001339526,0.0001822706,0.00005729375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005156812,"about_ca_system_score_gemma":0.00002454604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005364883,"about_ca_topic_score_gemma":2.248806e-7,"domain_scores_codex":[0.9989353,0.0001071755,0.0002378178,0.0001856923,0.000359457,0.0001745947],"domain_scores_gemma":[0.9990991,0.0002460041,0.00009779256,0.0003498387,0.000100513,0.0001067991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002109176,0.002489579,0.03432158,0.002194019,0.0004516456,0.000003725239,0.002595292,0.06781816,0.3074252,0.5240692,0.001488399,0.05693221],"study_design_scores_gemma":[0.00115082,0.001506895,0.1452789,0.005051879,0.0003003354,2.131775e-7,0.0001876619,0.02318722,0.8012716,0.003712055,0.01752081,0.0008315969],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976907,0.000168328,0.00008271262,0.0007058278,0.00001217635,0.0002250304,0.00001563372,0.0000091168,0.00109044],"genre_scores_gemma":[0.999495,0.0002195764,0.00002473746,0.00005128149,0.0001185324,0.00007371145,0.000002591551,0.000009070011,0.000005516157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5203572,"threshold_uncertainty_score":0.2811894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06851176769008432,"score_gpt":0.3434920695370104,"score_spread":0.2749803018469261,"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."}}