{"title":"理论群体遗传学的科学生产力:以核心期刊为例","authors":"B. Gupta, Suresh Kumar","doi":"10.17821/SRELS/1998/V35I2/48725","DOIUrl":null,"url":null,"abstract":"Examines the applicability of Lotka's Law and a few other statistical distributions for their goodness-of-fit to the author productivity data from eleven core journals in theoretical population genetics. The negative binomial and geometric distribution are found to be generally applicable in majority of the data sets and also in terms of best fit.","PeriodicalId":190905,"journal":{"name":"Library science with a slant to documentation and information studies","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Scientific Productivity in Theoretical Population Genetics:A Case Study in Core Journals\",\"authors\":\"B. Gupta, Suresh Kumar\",\"doi\":\"10.17821/SRELS/1998/V35I2/48725\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Examines the applicability of Lotka's Law and a few other statistical distributions for their goodness-of-fit to the author productivity data from eleven core journals in theoretical population genetics. The negative binomial and geometric distribution are found to be generally applicable in majority of the data sets and also in terms of best fit.\",\"PeriodicalId\":190905,\"journal\":{\"name\":\"Library science with a slant to documentation and information studies\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Library science with a slant to documentation and information studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17821/SRELS/1998/V35I2/48725\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Library science with a slant to documentation and information studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17821/SRELS/1998/V35I2/48725","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scientific Productivity in Theoretical Population Genetics:A Case Study in Core Journals
Examines the applicability of Lotka's Law and a few other statistical distributions for their goodness-of-fit to the author productivity data from eleven core journals in theoretical population genetics. The negative binomial and geometric distribution are found to be generally applicable in majority of the data sets and also in terms of best fit.
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