PREreview del <span class="word">Estimation <span class="word">of <span class="word">the <span class="word"><span class="changedDisabled">First <span class="word"><span class="changedDisabled">Maturity <span class="word"><span class="changedDisabled">Using <span class="word"><span class="changedDisabled">Machine <span class="word"><span class="changedDisabled">Learning <span class="word">of <span class="word"><span class="changedDisabled">Swimming <span class="word"><span class="changedDisabled">Crab (<em><span class="word italic">Portunus <span class="word italic">trituberculatus</em>) <span class="word">in <span class="word">the <span class="word">Yellow <span class="word">Sea <span class="word">of <span class="word">Korea

The title of this preprint on PREreview is funny, it contains a lot of meaningless wordings. Excluding those funny words, the content of the manuscript is about machine learning, we are not sure if the machine learning devices or applications caused such errors. Or else, it maybe a language translation error of the system.

<span class="word">Estimation <span class="word">of <span class="word">the <span class="word"><span class="changedDisabled">First <span class="word"><span class="changedDisabled">Maturity <span class="word"><span class="changedDisabled">Using <span class="word"><span class="changedDisabled">Machine <span class="word"><span class="changedDisabled">Learning <span class="word">of <span class="word"><span class="changedDisabled">Swimming <span class="word"><span class="changedDisabled">Crab (<em><span class="word italic">Portunus <span class="word italic">trituberculatus</em>) <span class="word">in <span class="word">the <span class="word">Yellow <span class="word">Sea <span class="word">of <span class="word">Korea

The true title should be:

Estimation of the First Maturity Using Machine Learning of Swimming Crab (Portunus trituberculatus) in the Yellow Sea of Korea

From our limited information technology knowledge, such discrepancies in the displayed title likely stem from the underlying HTML markup used by the platform (possibly a preprint aggregator like Scilit or a similar site, which aggregates content from sources like Preprints.org). These tags with classes like "word" and "changedDisabled" are not part of the actual manuscript title but are added in the web page's source code for technical purposes, such as:

• Change tracking or diff visualization: The "changedDisabled" class suggests a system for marking edited or revised text (e.g., from document versions or collaborative edits), where changes are noted but not actively shown or "disabled" in the final view. This could occur if the title was parsed from a document with track changes enabled, like in Microsoft Word or a content management system, and the platform retains the markup during aggregation.

• Word-level processing: Wrapping each word in allows for features like search term highlighting, accessibility enhancements (e.g., for screen readers), or interactive elements (e.g., tooltips, annotations, or JavaScript-driven behaviors in review platforms).

• Parsing or import artifacts: When pulling metadata from the original preprint server (e.g., Preprints.org), the aggregator might introduce this structure during HTML conversion, especially if the source involves formatted text like italics for scientific names, which can lead to nested tags.

In a browser, these tags are invisible, and the title renders cleanly as plain text. The "discrepancy" becomes apparent only when viewing the page source, inspecting elements in developer tools, or copying the content in a way that includes the raw HTML (e.g., via certain browser extensions or feeds). If the platform has a bug or incomplete sanitization, the tags might occasionally display as text, but that's less common. The true title is the unadorned version without this markup, as it's the canonical text from the preprint.

Competing interests

The authors declare that they have no competing interests.

Use of Artificial Intelligence (AI)

The authors declare that they did not use generative AI to come up with new ideas for their review.