Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis

Abstract With the accumulation of scientific information in natural science, even experts can find difficult to keep integrating new piece of information. It is critical to explore modelling solutions able to capture information scattered in publications as a computable representation form. Traditio...

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Autores principales:	Kamal Kansou, Caroline Rémond, Gabriel Paës, Estelle Bonnin, Jean Tayeb, Bert Bredeweg
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/06bca319873d4aa2bbe155c20a0d778d
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spelling	oai:doaj.org-article:06bca319873d4aa2bbe155c20a0d778d2021-12-02T15:06:07ZTesting scientific models using Qualitative Reasoning: Application to cellulose hydrolysis10.1038/s41598-017-14281-42045-2322https://doaj.org/article/06bca319873d4aa2bbe155c20a0d778d2017-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-14281-4https://doaj.org/toc/2045-2322Abstract With the accumulation of scientific information in natural science, even experts can find difficult to keep integrating new piece of information. It is critical to explore modelling solutions able to capture information scattered in publications as a computable representation form. Traditional modelling techniques are important in that regard, but relying on numerical information comes with limitations for integrating results from distinct studies, high-level representations can be more suited. We present an approach to stepwise construct mechanistic explanation from selected scientific papers using the Qualitative Reasoning framework. As a proof of concept, we apply the approach to modelling papers about cellulose hydrolysis mechanism, focusing on the causal explanations for the decreasing of hydrolytic rate. Two explanatory QR models are built to capture classical explanations for the phenomenon. Our results show that none of them provides sufficient explanation for a set of basic experimental observations described in the literature. Combining the two explanations into a third one allowed to get a new and sufficient explanation for the experimental results. In domains where numerical data are scarce and strongly related to the experimental conditions, this approach can aid assessing the conceptual validity of an explanation and support integration of knowledge from different sources.Kamal KansouCaroline RémondGabriel PaësEstelle BonninJean TayebBert BredewegNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-18 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kamal Kansou Caroline Rémond Gabriel Paës Estelle Bonnin Jean Tayeb Bert Bredeweg Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
description	Abstract With the accumulation of scientific information in natural science, even experts can find difficult to keep integrating new piece of information. It is critical to explore modelling solutions able to capture information scattered in publications as a computable representation form. Traditional modelling techniques are important in that regard, but relying on numerical information comes with limitations for integrating results from distinct studies, high-level representations can be more suited. We present an approach to stepwise construct mechanistic explanation from selected scientific papers using the Qualitative Reasoning framework. As a proof of concept, we apply the approach to modelling papers about cellulose hydrolysis mechanism, focusing on the causal explanations for the decreasing of hydrolytic rate. Two explanatory QR models are built to capture classical explanations for the phenomenon. Our results show that none of them provides sufficient explanation for a set of basic experimental observations described in the literature. Combining the two explanations into a third one allowed to get a new and sufficient explanation for the experimental results. In domains where numerical data are scarce and strongly related to the experimental conditions, this approach can aid assessing the conceptual validity of an explanation and support integration of knowledge from different sources.
format	article
author	Kamal Kansou Caroline Rémond Gabriel Paës Estelle Bonnin Jean Tayeb Bert Bredeweg
author_facet	Kamal Kansou Caroline Rémond Gabriel Paës Estelle Bonnin Jean Tayeb Bert Bredeweg
author_sort	Kamal Kansou
title	Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
title_short	Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
title_full	Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
title_fullStr	Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
title_full_unstemmed	Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis
title_sort	testing scientific models using qualitative reasoning: application to cellulose hydrolysis
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/06bca319873d4aa2bbe155c20a0d778d
work_keys_str_mv	AT kamalkansou testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis AT carolineremond testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis AT gabrielpaes testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis AT estellebonnin testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis AT jeantayeb testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis AT bertbredeweg testingscientificmodelsusingqualitativereasoningapplicationtocellulosehydrolysis
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Testing scientific models using Qualitative Reasoning: Application to cellulose hydrolysis

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