Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A widely used measure of scientific impact is citations. Hover, due to their heavy-tailed distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact,  address two analogous questions asked by many scientific researchers: “How will my  h -index evolve over time, and which of my previously or newly published papers will contribute to it?” To ansr these questions,  perform two related tasks. First,  develop a model to predict authors’ future  h -indices based on their current scientific impact. Second,  examine the factors that drive papers—either previously or newly published—to increase their authors’ predicted future  h -indices. By leveraging relevant factors,  can predict an author's  h -index in five years with an    $R^2$       value of 0.92 and whether a previously (newly) published paper will contribute to this future  h -index with an   $F_1$       score of 0.99 (0.77).  find that topical authority and publication venue are crucial to these effective predictions, while topic popularity is surprisingly inconsequential. Further,  develop an online tool that allows users to generate informed  h  -index predictions. Our work demonstrates the predictability of scientific impact, and can help researchers to effectively leverage their scholarly position of “standing on the shoulders of giants.”
['Yuxiao Dong', 'Reid A. Johnson', 'Nitesh V. Chawla']
I am writing a research paper on a idea Can Scientific Impact Be Predicted
[{"from": "human", "value": "I am writing a research paper on a idea Can Scientific Impact Be Predicted"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A widely used measure of scientific impact is citations. Hover, due to their heavy-tailed distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact,  address two analogous questions asked by many scientific researchers: \u201cHow will my  h -index evolve over time, and which of my previously or newly published papers will contribute to it?\u201d To ansr these questions,  perform two related tasks. First,  develop a model to predict authors\u2019 future  h -indices based on their current scientific impact. Second,  examine the factors that drive papers\u2014either previously or newly published\u2014to increase their authors\u2019 predicted future  h -indices. By leveraging relevant factors,  can predict an author's  h -index in five years with an    $R^2$       value of 0.92 and whether a previously (newly) published paper will contribute to this future  h -index with an   $F_1$       score of 0.99 (0.77).  find that topical authority and publication venue are crucial to these effective predictions, while topic popularity is surprisingly inconsequential. Further,  develop an online tool that allows users to generate informed  h  -index predictions. Our work demonstrates the predictability of scientific impact, and can help researchers to effectively leverage their scholarly position of \u201cstanding on the shoulders of giants.\u201d"}]