{"id":"W3095869417","doi":"10.1139/cjp-2019-0264","title":"An approach to the study of the thermally driven deconfinement phase transition in a finite volume through the order parameter, its derivatives, and cumulants of the probability distribution","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"High-Energy Particle Collisions Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Direction Générale de la Recherche Scientifique et du Développement Technologique","keywords":"Cumulant; Physics; Deconfinement; Phase transition; Probability distribution; Hadron; Distribution (mathematics); Quark–gluon plasma; Statistical physics; Finite volume method; Massless particle; Quark; Monte Carlo method; Phase (matter); Particle physics; Thermodynamics; Statistics; Quantum mechanics; Mathematical analysis; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002604814,0.00009315544,0.0001650255,0.00001125494,0.0001911592,0.00003932601,0.0004644213,0.00001564838,0.0000136978],"category_scores_gemma":[0.00006307058,0.00004451015,0.00006218133,0.0005501988,0.0001277658,0.0001246802,0.00003221932,0.000237972,3.357596e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003841894,"about_ca_system_score_gemma":0.0004621829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002471569,"about_ca_topic_score_gemma":0.00213143,"domain_scores_codex":[0.9987195,0.0004567818,0.0003061644,0.0001169617,0.0002293613,0.0001712499],"domain_scores_gemma":[0.9991199,0.00008072101,0.0001707966,0.0002693541,0.0002349246,0.0001242585],"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":[0.0001527711,0.001790913,0.05754959,0.00003116728,0.0002410424,0.000001748691,0.08329118,0.8379901,0.002491632,0.008348591,0.0001868657,0.007924418],"study_design_scores_gemma":[0.006715146,0.002103809,0.3350291,0.0001863291,0.0002451431,0.000002951524,0.03111415,0.6107503,0.009055826,0.00242713,0.00196889,0.0004012205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857924,0.00001400995,0.01139551,0.001880941,0.00002300281,0.0006977652,0.0001607583,6.740063e-7,0.00003490616],"genre_scores_gemma":[0.9997858,5.780918e-7,0.00007165621,0.00004455528,0.00006182737,0.00002078897,0.000004993353,0.000006467878,0.000003364154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2774795,"threshold_uncertainty_score":0.373629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0464649712141439,"score_gpt":0.2927081106743425,"score_spread":0.2462431394601986,"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."}}