AI Content Detector

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Overview

The AI Content Detector is a powerful node that analyzes text to determine whether it was written by a human or generated by AI. Using GPTZero’s advanced detection model, it provides reliable analysis with detailed insights and confidence scores.

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Quick Start

• Input: Text content to analyze (single piece or batch)
• Cost: 30 credits per 1,000 words
• Output: AI detection verdict, confidence score, detailed analysis
• Main use: Content verification, authenticity checks, plagiarism detection

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Core Features

1. Accurate Detection

   • Analyzes writing patterns and text structure
   • Provides confidence scores for reliability
   • Identifies mixed content (partially AI-generated)

2. Detailed Analysis

   • Writing style metrics
   • Sentence structure analysis
   • Word choice patterns
   • Readability scores

3. Batch Processing

   • Analyze multiple texts simultaneously
   • Efficient processing in Loop Mode
   • Consistent results across large datasets

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Input and Output Specifications

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Input Fields

• Content: Text to analyze (required)
  • Type: Text or List (in Loop Mode)
  • Format: Plain text

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Output Fields

1. AI Detection Result

   • Type: Text (String)
   • Possible values: “Human-written”, “AI-generated”, “Mixed”

2. Confidence Level

   • Range: 0-100%
   • Format: Decimal percentage

3. Detailed Message

   • Type: Text (String)
   • Includes: Reasoning for the result and key findings

4. Writing Statistics

   • Type: JSON Object
   • Contains: Readability metrics, sentence analysis, pattern detection

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Practical Workflow Examples

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1. Content Marketing Validation Pipeline

Goal: Validate blog posts and generate SEO metadata for approved content

Nodes Used:

1. AI Content Detector

   • Analyzes submitted content
   • Confidence threshold: 80%

2. Extract Data Node

   • Pulls key topics and themes
   • Identifies main keywords

3. Categorizer Node

   • Assigns content categories
   • Tags content type

4. Ask AI Node

   • Generates SEO meta descriptions
   • Creates social media snippets

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2. Academic Submission Review System

Goal: Screen student assignments for AI-generated content and provide detailed feedback

Workflow Steps:

1. PDF Reader Node

   • Extracts text from submissions
   • Maintains formatting

2. Text Formatter Node

   • Normalizes text structure

3. AI Content Detector

   • Analyzes content authenticity
   • Generates detailed reports

4. Scorer Node

   • Evaluates writing quality based on set rubric
   • Provides feedback points (enable AI Justification output)

5. Send Email Notification Node

   • Alerts instructors of potential issues
   • Sends automated feedback

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3. Content Moderation System

Goal: Review and categorize user-submitted content across multiple platforms

Integration Points:

1. Website Scraper Node

   • Extracts relevant text from article or blog

2. AI Content Detector

   • Screens for AI-generated content
   • Provides confidence scores

3. Categorizer Node

   • Classifies content type
   • Tags content themes

4. Airtable Database Writer Node

   • Stores analysis results
   • Updates content status

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Best Practices

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Optimization Tips

1. Batch Processing

   • Use Loop Mode for multiple content items

2. Credit Management

   • Estimate word count beforehand
   • Use Text Formatter, Find & Replace, or Chunk Text to clean input
   • Remove unnecessary content

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Limitations and Considerations

• Possible false positives
• Language support restrictions

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Additional Resources

• GPTZero Documentation
• Related nodes: Categorizer, Ask AI, Text Formatter