{"id":"W4322717438","doi":"10.48550/arxiv.2302.13852","title":"Rapidity scan with multistage hydrodynamic and statistical thermal models","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"High-Energy Particle Collisions Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Rapidity; Hadronization; Thermal; Physics; Nuclear physics; Beam (structure); Thermal physics; Phase diagram; Particle physics; Distribution (mathematics); Closure (psychology); Phase (matter); Thermodynamics; Hadron; Non-equilibrium thermodynamics; Optics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001628,0.0002594976,0.0002872693,0.0001429179,0.000219681,0.00009069154,0.0003632421,0.0001014663,0.0001593371],"category_scores_gemma":[0.000006230355,0.0002528558,0.00006569148,0.0002712836,0.0003772549,0.0001543092,0.0008628228,0.0005677177,0.0000719395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009216672,"about_ca_system_score_gemma":0.0002006548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273071,"about_ca_topic_score_gemma":0.0001750885,"domain_scores_codex":[0.9983784,0.0001576117,0.0001344955,0.0007947711,0.0001212298,0.0004135121],"domain_scores_gemma":[0.9988084,0.0001641749,0.00007945836,0.0005942301,0.00009511659,0.0002586649],"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":[0.00007141116,0.0000732217,0.008205628,0.00002581168,0.0001251054,0.0001467705,0.00006288303,0.7921274,0.00006246361,0.1989028,0.00003769309,0.0001588215],"study_design_scores_gemma":[0.0006221322,0.00004057761,0.005026688,0.00005142344,0.00006136069,3.511644e-7,0.0001330203,0.9837378,0.00003927019,0.009970068,0.0000273696,0.0002899897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7915753,0.000004444908,0.2058783,0.00002299368,0.00004765359,0.000220942,0.0003387722,0.00007378753,0.001837817],"genre_scores_gemma":[0.9950179,0.0000124319,0.0004732771,0.000001327226,0.00006009988,0.000003938534,0.000124434,0.00004227463,0.004264266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.205405,"threshold_uncertainty_score":0.9999924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08417065783299377,"score_gpt":0.2174765888623128,"score_spread":0.133305931029319,"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."}}