This AI Tool Could Replace Half Your PhD Work (Here’s How to Use It Safely)

AnswerThis: Academic & Research Workflows - A Detailed Summary

Key Concepts:

AnswerThis: An AI-powered research assistant aiming to streamline the academic workflow from initial inquiry to publication.
Inquiry: Quick question & answer service with research paper filtering.
Full Review: Comprehensive literature review generation with customizable settings.
Canvas: The central workspace for interacting with search results, performing analysis, and generating outputs.
Notebook: A document editor within AnswerThis for formatting, editing, and exporting research content.
Biblometric Analysis: Visual representation of research data, including citations, authors, and keywords.
Agents (Coming Soon): Future functionality promising automated research tasks.
Citation Map: A visual network of papers citing a chosen origin paper.

I. Introduction & Pricing

The video focuses on AnswerThis, an AI tool designed to assist academics and researchers throughout the entire research process. While acknowledging the tool’s potential, the presenter notes its complexity. A special 25% discount on the monthly fee has been secured for viewers, aiming to make the tool more accessible compared to other AI options. The core proposition of AnswerThis is to be an “all-in-one research assistant,” moving from question to final publication.

II. Two Core Offerings: Inquiry vs. Full Review

AnswerThis offers two primary functionalities: a simple inquiry service and a full literature review generation.

Inquiry: This allows users to quickly pose a question and receive a concise answer filtered through research papers, the internet, or uploaded library materials. Results are presented as both text and a table, accessible through the “Canvas.” The power lies in the filtering options, allowing specification of citation count, journal quality, publication type, and date range. An example query, “how do exfoliants enhance skin texture,” demonstrates a clear, referenced response with easily accessible citations.
Full Review: This feature generates a more in-depth literature review based on user-defined parameters. It’s more powerful but also more complex, requiring a clear understanding of the available settings.

III. The Full Review Workflow & Canvas Functionality

The “Full Review” process begins with a research question and utilizes detailed literature review settings. Key settings include:

Number of Main Sections: Defining the structure of the review.
Subpoints per Section: Controlling the granularity of each section.
Topics to Cover: Specifying areas of focus.
Minimum Citations: Setting a threshold for paper inclusion (e.g., 20+ citations).
Journal Quality: Filtering by journal quartile (e.g., Q2).
Publication Date Range: Focusing on recent or historical research.

After initiating the review (which takes approximately 5 minutes), a comprehensive draft is generated, complete with headings, tables, and references. The tool initially presents results in a column-based format, but a more readable single-column layout is preferred. In the example provided, a search yielded 372 papers, but only 14 were included in the initial review draft.

The Canvas is the central hub for interacting with the generated review. Key functionalities within the Canvas include:

Follow-up Questions: Asking clarifying questions about the review content, generating further insights.
Notebook: A built-in document editor (similar to Google Docs) for formatting, highlighting, and exporting the generated text. Content can be added to and saved within the user’s library.
Chat with Papers: Selecting papers from the search results and engaging in a conversational interface to ask specific questions about their findings, limitations, or methodologies. Filtering by publication date (e.g., 2020 onwards) is possible before initiating the chat.
Create a New Table: Generating a customized table from the selected papers, allowing users to add columns to extract specific data points (e.g., research gaps, future work).
Biblometric Analysis: Visualizing research data, including publications by year, citations by year, citation impact, word clouds, and top authors.
Search New Papers: Initiating a new search directly from the Canvas, expanding the research scope.
Agents (Coming Soon): Future functionality promising automated research tasks.

IV. Advanced Features: Biblometric Analysis & Citation Maps

Biblometric Analysis: This feature provides a visual overview of the research landscape, identifying trends, key authors, and influential publications. It can be customized to focus on specific time periods or subsets of the search results.
Citation Map: Starting with an “origin” paper, this feature generates a network visualization of papers that cite it, revealing the interconnectedness of research within a field. Options include filtering by most cited, most connected, and top contributing authors.
Diagrams: The tool also offers diagram creation capabilities (mind maps, user journeys), though the presenter anticipates the graph visualizations to be particularly powerful.

V. Integration & Export

The Notebook feature allows seamless integration of findings from various Canvas functionalities. Information generated through follow-up questions, chats with papers, or table creation can be easily added to the Notebook for further refinement and export.

VI. Conclusion

AnswerThis is a powerful, albeit complex, AI tool with the potential to significantly streamline the academic research process. Its strength lies in its comprehensive feature set and the ability to move from initial inquiry to a draft literature review within a single platform. Understanding the various functionalities and the Canvas workflow is crucial for maximizing its effectiveness. The presenter encourages viewers to explore the tool and leverage the provided discount to assess its value for their individual research needs. Future development of the “Agents” feature is anticipated to further enhance its capabilities.