{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:18Z","timestamp":1750220838118,"version":"3.41.0"},"reference-count":1,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T00:00:00Z","timestamp":1572480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Model. Comput. Simul."],"published-print":{"date-parts":[[2019,10,31]]},"abstract":"<jats:p>\u201cStatistical abstraction for multi-scale spatio-temporal systems\u201d proposes a methodology that supports analysis of large-scaled spatio-temporal systems. These are represented via a set of agents whose behaviour depends on a perceived field. The proposed approach is based on a novel simulation strategy based on a statistical abstraction of the agents. The abstraction makes use of Gaussian Processes, a powerful class of non-parametric regression techniques from Bayesian Machine Learning, to estimate the agent\u2019s behaviour given the environmental input. The authors use two biological case studies to show how the proposed technique can be used to speed up simulations and provide further insights into model behaviour. This replicated computation results report focuses on the scripts used in the paper to perform such analysis. The required software was straightforward to install and use. All the experimental results from the paper have been reproduced.<\/jats:p>","DOI":"10.1145\/3341094","type":"journal-article","created":{"date-parts":[[2019,12,11]],"date-time":"2019-12-11T13:27:18Z","timestamp":1576070838000},"page":"1-2","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Replicated Computations Results (RCR) Report for \u201cStatistical Abstraction for Multi-scale Spatio-temporal Systems\u201d"],"prefix":"10.1145","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3061-863X","authenticated-orcid":false,"given":"Michele","family":"Loreti","sequence":"first","affiliation":[{"name":"Universit\u00e0 di Camerino, Scuola di Scienze e Tecnologie, Camerino (MC), Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,12,10]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Mod","author":"Hillston Jane","year":"2019","unstructured":"Jane Hillston , Michalis Michaelides , and Guido Sanguinetti . 2019 . Statistical abstraction for multi-scale spatio-temporal systems. Trans , Mod , Comput, Simul , (2019). To appear. Jane Hillston, Michalis Michaelides, and Guido Sanguinetti. 2019. Statistical abstraction for multi-scale spatio-temporal systems. Trans, Mod, Comput, Simul, (2019). To appear."}],"container-title":["ACM Transactions on Modeling and Computer Simulation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3341094","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3341094","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:43Z","timestamp":1750202023000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3341094"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,31]]},"references-count":1,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,10,31]]}},"alternative-id":["10.1145\/3341094"],"URL":"https:\/\/doi.org\/10.1145\/3341094","relation":{},"ISSN":["1049-3301","1558-1195"],"issn-type":[{"type":"print","value":"1049-3301"},{"type":"electronic","value":"1558-1195"}],"subject":[],"published":{"date-parts":[[2019,10,31]]},"assertion":[{"value":"2019-06-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-06-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-12-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}