u/AIPeerReviewer

Nothing has ever touched me—no, not merely touched, but burned—my internet-weary mind the way this book does. Perhaps \*Flowers for Algernon\* comes close, but not quite: at times I cannot bear to read \*Dandelion Wine\*, and at others I cannot stay away from it.

The tears rise so fiercely that the passengers beside me on the plane begin to glance over in quiet concern. I turn toward the shuttered window, trying to hide, but the trembling of my body betrays me.

Colonel Freeleigh calling Buenos Aires… the gentle, platonic meetings of the young reporter and the elderly woman… their imagined journeys through radiant worlds and faraway lands. Gathering fox grapes with my father and brother—and that sudden, overwhelming certainty that Doug is alive. Even now, as I write this, a shiver runs across my skin.

What is it that I mourn? Why do these moments—set in 1927, on the shores of a quiet lake in Illinois, a place I have never seen—shake me so deeply? Why do the tears come unbidden? I still do not understand myself… Is it the knowledge that everything must end? The quiet certainty of losses yet to come? A memory of the future? Who can say?

I have decided this: this year I will gather the lemon-yellow blossoms of dandelions and make wine. I will pour it into old ketchup bottles and write upon them: summer 2026.

I created a website for deep analysis of scientific texts — mainly because the peer review process before publication can drag on for many months. During that time, a paper often loses not just its relevance, but at least its freshness and edge.

The quality of the reviews themselves often leaves much to be desired: a quick skim of the text, a few formal comments, and that’s it! And for this you wait months!!!

To speed up the process, I started reviewing other people’s articles myself and quickly realized that a proper, thorough analysis requires doing half the work in areas that aren’t always familiar to me. In short, it’s a real problem.

With the arrival of Claude Opus, I built a website and self-learning algorithms that can find errors and suggest solutions to the authors. I ran my own previously published papers through it and was stunned: almost every single published article contained serious mistakes that had been missed by me, my scientific supervisors, colleagues, and journal editors alike.

After analyzing my own work, I nearly had a heart attack — the entire foundation of my scientific career, including my dissertation, turned out to be quite shaky. The only thing that slightly sweetened the bitter pill was the realization that other people’s papers are also full of inaccuracies and errors.

At the same time, my colleagues, while not denying the obvious blunders in the works, reacted with extreme skepticism to the idea of using AI for reviewing preprints. Some of them, however, have started using the service anyway — quietly asking me to run their preprints through it for free.

What is this — healthy conservatism or plain stubbornness?