Studies proposing new determinants of corporate innovation include previously identified factors in an ad hoc manner. We find that only a sparse set of recently proposed innovation determinants provide material, independent information about patents and citations. We document that inferences in recent empirical studies often change when we include previously discovered innovation determinants. Commonly used econometric methods, including fixed effects and plausible shocks, do not always mitigate the need to condition on previously identified innovation determinants. Rather than randomly selecting a subset of control variables from prior studies, our analysis offers researchers a framework to consider previously proposed variables.
{"title":"Disregarding the Shoulders of Giants: Inferences from Innovation Research","authors":"D. Reeb, Wanli Zhao","doi":"10.2139/ssrn.3175055","DOIUrl":"https://doi.org/10.2139/ssrn.3175055","url":null,"abstract":"\u0000 Studies proposing new determinants of corporate innovation include previously identified factors in an ad hoc manner. We find that only a sparse set of recently proposed innovation determinants provide material, independent information about patents and citations. We document that inferences in recent empirical studies often change when we include previously discovered innovation determinants. Commonly used econometric methods, including fixed effects and plausible shocks, do not always mitigate the need to condition on previously identified innovation determinants. Rather than randomly selecting a subset of control variables from prior studies, our analysis offers researchers a framework to consider previously proposed variables.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116226713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How do firms and inventors move through knowledge space as they develop their innovations? We propose a method for tracking patterns of exploration and exploitation in patenting behaviour in the US for the period since 1920. Our exploration measure is constructed from the text of patents and involves the use of Bayesian Surprise to measure how different current patent-based innovations are from existing portfolios. Our results indicate that there are distinct life-cycle patterns to firm and inventor exploration. Furthermore, exploration activity is more geographically concentrated than general patenting, but this concentration is centred outside the main hubs of patenting.
{"title":"Exploration and Exploitation in US Technological Change","authors":"Vasco M. Carvalho, M. Draca, Nikolas Kuhlen","doi":"10.2139/ssrn.3900479","DOIUrl":"https://doi.org/10.2139/ssrn.3900479","url":null,"abstract":"How do firms and inventors move through knowledge space as they develop their innovations? We propose a method for tracking patterns of exploration and exploitation in patenting behaviour in the US for the period since 1920. Our exploration measure is constructed from the text of patents and involves the use of Bayesian Surprise to measure how different current patent-based innovations are from existing portfolios. Our results indicate that there are distinct life-cycle patterns to firm and inventor exploration. Furthermore, exploration activity is more geographically concentrated than general patenting, but this concentration is centred outside the main hubs of patenting.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122310057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a graduate student at the Center for Adaptive Behavior and Cognition (ABC), I learned that simple models can beat more complex models, particularly in out-of-sample accuracy. This finding has been validated in my career since then. But I did observe some situations where complex models were useful. And even more surprisingly, I noticed some situations where complex models were truly necessary. The model was driven to complexity by an arms race. I will illustrate such an arms race with a series of diagrams showing how a classifier can be driven to complexity, focusing on the case of spam.
Talk at “Decision Making Under Radical Uncertainty”, June 11-12, 2021. Berlin, Germany (digital) Talk recording: https://vimeo.com/568707053
{"title":"The Arms Race of Models: Complexify or Die","authors":"J. Whitmore","doi":"10.2139/ssrn.3867464","DOIUrl":"https://doi.org/10.2139/ssrn.3867464","url":null,"abstract":"As a graduate student at the Center for Adaptive Behavior and Cognition (ABC), I learned that simple models can beat more complex models, particularly in out-of-sample accuracy. This finding has been validated in my career since then. But I did observe some situations where complex models were useful. And even more surprisingly, I noticed some situations where complex models were truly necessary. The model was driven to complexity by an arms race. I will illustrate such an arms race with a series of diagrams showing how a classifier can be driven to complexity, focusing on the case of spam.<br><br>Talk at “Decision Making Under Radical Uncertainty”, June 11-12, 2021. Berlin, Germany (digital)<br>Talk recording: https://vimeo.com/568707053","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133398943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The conventional wisdom classifies technologies into dichotomous types, such as competence-enhancing versus competence-destroying or sustaining versus disruptive. This categorization corresponds to the two routes of technology evolution: either consolidating or destabilizing past achievements. However, the combinational view suggests that a technology is a recombination of existing components, and hence it may consolidate some of its prior arts while destabilizing others. Therefore, we propose a dual technology can be simultaneously destabilizing and consolidating. To identify dual technologies, we develop the destabilization index (D) and the consolidation index (C) using patent citation networks. To validate the proposed indexes, we first select representative US patent examples to illustrate the face validity by showing how D and C indexes capture the dual characteristics. Secondly, we assess convergent and discriminant validity by examining the correlations between D and C indexes and other innovation measures. Finally, we evaluate nomological validity by studying the antecedents and the predictive power of the dual characteristics using 2.6 million patents from USPTO's dataset from 1976 to 2006. Regression results show that theory-driven factors such as patent novelty and government interest are associated with D and C indexes as expected. We also find that high D and C indexes are positively associated with patent value as perceived by its owner, and entity size moderates the effects of D and C indexes on patent value differently.
{"title":"Destabilization and Consolidation: Conceptualizing, Measuring, and Validating the Dual Characteristics of Technology","authors":"Jiyao Chen, Diana Shao, Shaokun Fan","doi":"10.2139/ssrn.3682843","DOIUrl":"https://doi.org/10.2139/ssrn.3682843","url":null,"abstract":"Abstract The conventional wisdom classifies technologies into dichotomous types, such as competence-enhancing versus competence-destroying or sustaining versus disruptive. This categorization corresponds to the two routes of technology evolution: either consolidating or destabilizing past achievements. However, the combinational view suggests that a technology is a recombination of existing components, and hence it may consolidate some of its prior arts while destabilizing others. Therefore, we propose a dual technology can be simultaneously destabilizing and consolidating. To identify dual technologies, we develop the destabilization index (D) and the consolidation index (C) using patent citation networks. To validate the proposed indexes, we first select representative US patent examples to illustrate the face validity by showing how D and C indexes capture the dual characteristics. Secondly, we assess convergent and discriminant validity by examining the correlations between D and C indexes and other innovation measures. Finally, we evaluate nomological validity by studying the antecedents and the predictive power of the dual characteristics using 2.6 million patents from USPTO's dataset from 1976 to 2006. Regression results show that theory-driven factors such as patent novelty and government interest are associated with D and C indexes as expected. We also find that high D and C indexes are positively associated with patent value as perceived by its owner, and entity size moderates the effects of D and C indexes on patent value differently.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patent classification systems and upper-level grouping datasets have been widely used for research and entrepreneurial purposes but are insufficiently documented. This article provides an overview of the major patent classification systems and the basic ideas behind categorization of the data on patent classes. I highlight recent institutional changes that disproportionately affect patents in specific categories and alternative categorizations used in the patent examination process. Finally, I update the National Bureau of Economic Research patent technological categorization based on the latest U.S. patent classification. The resulting datasets can be used in numerous follow-up analyses using patent data to investigate innovation and entrepreneurship.
{"title":"Patent Classification Systems and Technological Categorization: An Overview and Data Update","authors":"Lucy Xiaolu Wang","doi":"10.2139/ssrn.3220033","DOIUrl":"https://doi.org/10.2139/ssrn.3220033","url":null,"abstract":"Patent classification systems and upper-level grouping datasets have been widely used for research and entrepreneurial purposes but are insufficiently documented. This article provides an overview of the major patent classification systems and the basic ideas behind categorization of the data on patent classes. I highlight recent institutional changes that disproportionately affect patents in specific categories and alternative categorizations used in the patent examination process. Finally, I update the National Bureau of Economic Research patent technological categorization based on the latest U.S. patent classification. The resulting datasets can be used in numerous follow-up analyses using patent data to investigate innovation and entrepreneurship.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131981864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diogo Ferraz, H. F. Moralles, N. D. Costa, D. Rebelatto
Several studies argue that economic growth cannot well explain human development. The economic complexity approach is an alternative understanding of how economic sophistication can affect well-being. Moreover, there is increasing literature using traditional Data Envelopment Analysis (DEA) models to measure the transformation of wealth into human development. However, we did not find studies comparing more advanced models, such as Slack Based Models (SBM), and which considers the economic sophistication as an input to generate human development. To fill this gap, the aim of this article is to compare traditional and SBM-DEA models, measuring the countries' efficiency in converting economic complexity into human development. We analyzed 50 countries through Data Envelopment Analysis (DEA) in 2013, comparing Constant and Variable returns of scale traditional and Slack Based models. We also proposed the Composite Index of Human Development and Economic Complexity (CIHD-EC). Our findings show that the traditional variable return of scale model tends to overestimate efficient countries. It occurs especially in developed and rich economies. In contrast, the slack-based model provides a better understanding of the problem under analysis. Finally, our CIHD-EC shows that only Singapore is efficient to transform economic complexity into human development around the world.
{"title":"Economic Complexity and Human Development: Comparing Traditional and Slack Based Data Envelopment Analysis Models","authors":"Diogo Ferraz, H. F. Moralles, N. D. Costa, D. Rebelatto","doi":"10.2139/ssrn.3402211","DOIUrl":"https://doi.org/10.2139/ssrn.3402211","url":null,"abstract":"Several studies argue that economic growth cannot well explain human development. The economic complexity approach is an alternative understanding of how economic sophistication can affect well-being. Moreover, there is increasing literature using traditional Data Envelopment Analysis (DEA) models to measure the transformation of wealth into human development. However, we did not find studies comparing more advanced models, such as Slack Based Models (SBM), and which considers the economic sophistication as an input to generate human development. To fill this gap, the aim of this article is to compare traditional and SBM-DEA models, measuring the countries' efficiency in converting economic complexity into human development. We analyzed 50 countries through Data Envelopment Analysis (DEA) in 2013, comparing Constant and Variable returns of scale traditional and Slack Based models. We also proposed the Composite Index of Human Development and Economic Complexity (CIHD-EC). Our findings show that the traditional variable return of scale model tends to overestimate efficient countries. It occurs especially in developed and rich economies. In contrast, the slack-based model provides a better understanding of the problem under analysis. Finally, our CIHD-EC shows that only Singapore is efficient to transform economic complexity into human development around the world.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121665267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew P. Motta, D. Chapman, Kathryn Haglin, D. Kahan
Science curious people -- those who enjoy consuming science-related information -- are less likely to hold polarized views about contentious science. Consequently, science curiosity is of great interest to scholars across the social sciences. However, measuring science curiosity via the science curiosity scale (SCS; Kahan et al., 2017) is highly time intensive; potentially impeding its widespread usage. In this paper, we present two new methods for reducing SCS administration time. One method presents respondents with a randomly selected subset of items (the "Random Subset Method; RS"). The other asks all respondents a core set of just four items (the "Reduced-Form Method; RF"). In three nationally representative surveys of U.S. adults, we assess the construct, convergent, and predictive validity of these alternatives. Across studies, the RS and RF versions of the SCS appear to be well validated. We conclude by discussing how researchers can apply these insights into their own research.
{"title":"Reducing the Administrative Demands of the Science Curiosity Scale (SCS): A Validation Study","authors":"Matthew P. Motta, D. Chapman, Kathryn Haglin, D. Kahan","doi":"10.2139/ssrn.3379265","DOIUrl":"https://doi.org/10.2139/ssrn.3379265","url":null,"abstract":"Science curious people -- those who enjoy consuming science-related information -- are less likely to hold polarized views about contentious science. Consequently, science curiosity is of great interest to scholars across the social sciences. However, measuring science curiosity via the science curiosity scale (SCS; Kahan et al., 2017) is highly time intensive; potentially impeding its widespread usage. In this paper, we present two new methods for reducing SCS administration time. One method presents respondents with a randomly selected subset of items (the \"Random Subset Method; RS\"). The other asks all respondents a core set of just four items (the \"Reduced-Form Method; RF\"). In three nationally representative surveys of U.S. adults, we assess the construct, convergent, and predictive validity of these alternatives. Across studies, the RS and RF versions of the SCS appear to be well validated. We conclude by discussing how researchers can apply these insights into their own research.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133681805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This project is an application of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in the field of object detection and classification. CNN's are best applicable in image and video recognition. The system proposed in this project involves training the network over images and processing the input video frames for testing. The model will be trained over images of potholes, road signs and pedestrians. The dataset of images for potholes is created, as there is no specific dataset available. The dataset of images for road signs and pedestrians is created by collecting images from various sources and formatting them. The model will be trained over these datasets and tested on a real time video. This is a prototype which can be implemented in automated cars and can be used by car drivers as an Android application, which detects the objects and alerts the user through a voice message.
{"title":"Review on Methodologies of Object Detection","authors":"Sumesh Shetty, Aditi Sharma, Apurva Patil, Atul Patil","doi":"10.2139/ssrn.3361545","DOIUrl":"https://doi.org/10.2139/ssrn.3361545","url":null,"abstract":"This project is an application of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in the field of object detection and classification. CNN's are best applicable in image and video recognition. The system proposed in this project involves training the network over images and processing the input video frames for testing. The model will be trained over images of potholes, road signs and pedestrians. The dataset of images for potholes is created, as there is no specific dataset available. The dataset of images for road signs and pedestrians is created by collecting images from various sources and formatting them. The model will be trained over these datasets and tested on a real time video. This is a prototype which can be implemented in automated cars and can be used by car drivers as an Android application, which detects the objects and alerts the user through a voice message.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130957762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
What are the determinants of creativity, innovation and impact? In this paper I explore this question through an analysis of data from the Song Explorer podcast, where composers describe how they created a specific song. I mine their accounts to classify their processes into seven different, but not mutually exclusive, theories of the creative process. The result of this exercise suggests that the recombination of existing songs is a major process for the creation of new successful songs. The second step considers what kind of recombinations are associated with high impact. For each song in the sample I have one or more other songs which were explicitly indicated as an influence or inspiration. I use the music genre classification system Every Noise at Once, that provides a map of over 1,800 genres and millions of songs to create a set of descriptive statistics of the similarity of each song to their inspiration-songs. These statistics are then used as explanatory variables in a regression that seeks to explain impact (YouTube views per day since the songs' video release), while controlling for other determinants of song impact, such as the artists’ established level of popularity. The results confirm the optimal differentiation hypothesis that the simultaneous presence of conventionality together with novelty, and not just one or the other, is a major determinant of creativity and impact.
创造力、创新和影响力的决定因素是什么?在本文中，我通过分析来自Song Explorer播客的数据来探讨这个问题，其中作曲家描述了他们如何创作特定的歌曲。我对他们的描述进行了挖掘，将他们的创作过程分为七种不同的、但并非相互排斥的创作过程理论。这个练习的结果表明，现有歌曲的重组是创造新成功歌曲的主要过程。第二步考虑什么样的重组与高影响相关。对于样本中的每首歌，我都有一首或多首其他歌曲明确表示为影响或灵感。我使用音乐类型分类系统Every Noise at Once，它提供了超过1800种类型和数百万首歌曲的地图，以创建一组描述性统计数据，显示每首歌曲与其灵感歌曲的相似性。然后，这些统计数据被用作回归中的解释变量，试图解释影响(自歌曲视频发布以来，YouTube每天的浏览量)，同时控制歌曲影响的其他决定因素，例如艺术家的既定受欢迎程度。结果证实了最优分化假设，即传统与新颖性的同时存在，而不仅仅是一个或另一个，是创造力和影响力的主要决定因素。
{"title":"Where’d You Get that Idea? Determinants of Creativity and Impact in Popular Music","authors":"Bernardo Mueller","doi":"10.2139/ssrn.3500916","DOIUrl":"https://doi.org/10.2139/ssrn.3500916","url":null,"abstract":"What are the determinants of creativity, innovation and impact? In this paper I explore this question through an analysis of data from the Song Explorer podcast, where composers describe how they created a specific song. I mine their accounts to classify their processes into seven different, but not mutually exclusive, theories of the creative process. The result of this exercise suggests that the recombination of existing songs is a major process for the creation of new successful songs. The second step considers what kind of recombinations are associated with high impact. For each song in the sample I have one or more other songs which were explicitly indicated as an influence or inspiration. I use the music genre classification system Every Noise at Once, that provides a map of over 1,800 genres and millions of songs to create a set of descriptive statistics of the similarity of each song to their inspiration-songs. These statistics are then used as explanatory variables in a regression that seeks to explain impact (YouTube views per day since the songs' video release), while controlling for other determinants of song impact, such as the artists’ established level of popularity. The results confirm the optimal differentiation hypothesis that the simultaneous presence of conventionality together with novelty, and not just one or the other, is a major determinant of creativity and impact.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127210168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work investigates the relationship between proxies of innovation activities, such as patents and trademarks, and firm performance in terms of revenues and growth. By resorting to the virtual universe of Italian manufacturing firms we provide a rather complete picture of the innovation activities of Italian firms, in terms of patents and trademarks, and we study whether the two instruments for protecting Intellectual Property (IP) exhibit complementarity or substitutability. In addition, and to our knowledge novel, we propose a measure of concordance (or proximity) between the patents and trademarks owned by the same firm and we then investigate whether such concordance appears to exert any effect on performance.
{"title":"Concordance and Complementarity in Intellectual Property Instruments","authors":"Marco Grazzi, C. Piccardo, C. Vergari","doi":"10.2139/ssrn.3316020","DOIUrl":"https://doi.org/10.2139/ssrn.3316020","url":null,"abstract":"This work investigates the relationship between proxies of innovation activities, such as patents and trademarks, and firm performance in terms of revenues and growth. By resorting to the virtual universe of Italian manufacturing firms we provide a rather complete picture of the innovation activities of Italian firms, in terms of patents and trademarks, and we study whether the two instruments for protecting Intellectual Property (IP) exhibit complementarity or substitutability. In addition, and to our knowledge novel, we propose a measure of concordance (or proximity) between the patents and trademarks owned by the same firm and we then investigate whether such concordance appears to exert any effect on performance.","PeriodicalId":346559,"journal":{"name":"Innovation Measurement & Indicators eJournal","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133448465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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