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What are the model essay types of double-blind experimental papers?
There are several types of model essays in double-blind experimental papers:

1. Descriptive research: This kind of paper mainly describes the design, implementation and results of a double-blind experiment. The author usually explains in detail why the double-blind design is chosen, and how this design can help reduce bias and improve the reliability of experimental results.

2. Methodology papers: These papers mainly focus on the methodological issues of double-blind experiments, such as how to select and train subjects, how to randomize and allocate, how to process data, etc. Authors usually describe these steps in detail and explain how they can help achieve double-blindness.

3. Systematic review and meta-analysis: This kind of paper mainly evaluates and analyzes the results of several double-blind experiments. Authors usually use statistical methods to compare the results of different experiments to determine whether double-blind design can really improve the credibility of experimental results.

4. Case report: This kind of paper mainly reports the specific results of one or several double-blind experiments. Authors usually describe the process and results of each experiment in detail, and their explanations for these results.

5. Review papers: This paper mainly reviews the research progress of double-blind experiments. The author usually summarizes the latest research results, discusses the advantages and disadvantages of double-blind experiments, and the future research direction.

6. Practical guide: This kind of paper mainly provides practical guide on how to design and implement double-blind experiments. The author usually provides detailed steps and suggestions to help other researchers conduct double-blind experiments more effectively.

The above are the main composition types of double-blind experimental papers. Different types of papers have different writing focuses and methods, but all require the author to have solid experimental design and data analysis capabilities, as well as a deep understanding of double-blind experiments.