Scienctific Paper Guide
Put paper name or pdf to read. it will summarize wildly. If you want to get the meaning of glossary, write G.
The Guide GPT helps users to quickly understand scientific papers and justifies the necessary information for a comprehensible understanding. Using this GPT system is straightforward - simply input the paper name or provide a PDF to be analyzed and transformed into a concise summary. If you need clarification on a specific term in the paper, simply type "G" and the GPT system will summarize the meaning of the glossary. Without access to additional knowledge features, the Guide GPT is solely focused on assisting users in understanding complex scientific papers.
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Learn how to use Scienctific Paper Guide effectively! Here are a few example prompts, tips, and the documentation of available commands.
Scientific Paper Guide
To interact with a custom GPT, you can use the following example prompts and commands:
Summary command
Syntax: ./summary paper-name
Description: Generates a summary of the paper's contents.
Example code: ./summary "Nature Neural Networks"
Expected output:
Summary of Nature Neural Networks:
In this paper, the authors present a novel architecture for deep learning in the field of neural networks. The paper outlines a method for training and analyzing complex neural networks, and presents several case studies to demonstrate the effectiveness of the approach.
Glossary command
Syntax: ./glossary paper-name
Description: Provides definitions for any glossary terms used in the paper.
Example code: ./glossary "Nature Neural Networks"
Expected output:
Glossary definitions for Nature Neural Networks:
- Deep learning: a subset of machine learning that focuses on the use of neural networks and other techniques inspired by the structure and function of the brain.
- Neural networks: a machine learning model inspired by the structure and function of the human nervous system, consisting of layers of interconnected nodes or neurons that process input information and produce output decisions.
- Gradient descent: an optimization algorithm used to minimize the errors in a neural network by adjusting the weights of the connections between nodes.
Quality command
Syntax: ./quality paper-name
Description: Evaluates the overall quality and credibility of the paper.
Example code: ./quality "Nature Neural Networks"
Expected output:
Quality and credibility evaluation for Nature Neural Networks:
The paper appears to be well-written and well-researched, with a clear and concise introduction, well-structured methods and results, and a comprehensive conclusion.
The authors have cited several respected sources and provided evidence to support their claims. However, it is important to note that the paper's findings should be further validated through additional research and experimentation.
Tools command
Syntax: ./tools
Description: Lists any additional tools or resources available through the GPT.
Example code: ./tools
Expected output:
Available tools and resources:
- Jupyter Notebook: a free, open-source interactive computing environment for creating and sharing documents that contain live code, equations, visualizations, and narrative text.
- TensorBoard: an open-source platform for building and sharing machine learning models and experiments.
- PyTorch: a popular open-source software library for data science and machine learning.