{"id":"W2606578885","doi":"10.1139/cjp-2016-0911","title":"An investigation of Renyi entropy in high-energy nucleus–nucleus collisions","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Physics","topic":"High-Energy Particle Collisions Research","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii; Autoritatea Natională pentru Cercetare Stiintifică; Joint Institute for Nuclear Research; Jadavpur University","keywords":"Physics; Nuclear emulsion; Logarithm; Multiplicity (mathematics); Rényi entropy; Projectile; Nucleus; Nuclear physics; Entropy (arrow of time); Atomic physics; Thermodynamics; Principle of maximum entropy; Statistics; Quantum mechanics","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":[0.0002700397,0.0001321288,0.0002984193,0.0002057892,0.0003671747,0.0001841506,0.0007387434,0.00005105408,0.0001186987],"category_scores_gemma":[0.00004733519,0.0001291897,0.0001016936,0.0002436355,0.0002703367,0.0007064156,0.00003307357,0.0002552485,0.000008644303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001318369,"about_ca_system_score_gemma":0.001654168,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05199113,"about_ca_topic_score_gemma":0.01019966,"domain_scores_codex":[0.9986512,0.0001224104,0.000440927,0.0001500127,0.0002723168,0.0003631272],"domain_scores_gemma":[0.9977103,0.00005580867,0.0004611393,0.0005923115,0.0003985797,0.0007818032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002401895,0.00009037023,0.2682762,0.000005848541,0.00006534527,0.00005077121,0.0007003334,0.01528922,0.01168108,0.6975608,0.0008222036,0.005433849],"study_design_scores_gemma":[0.005815943,0.001089375,0.6850123,0.0006426201,0.0001381817,0.00001123367,0.001655438,0.04919362,0.1094348,0.1390504,0.006937894,0.001018242],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972791,0.00001573214,0.001542852,0.000299887,0.0002029226,0.00005410961,0.00009779889,0.000002239056,0.0005053583],"genre_scores_gemma":[0.9983693,0.000003812012,0.001030584,0.00001081266,0.0004540658,0.000003353689,0.00001304843,0.00002426183,0.00009072421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5585104,"threshold_uncertainty_score":0.9543217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100631678119497,"score_gpt":0.2721309747771735,"score_spread":0.2511246579959785,"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."}}