import type { Metadata } from "next";
import Link from "next/link";

export const metadata: Metadata = { title: "About", alternates: { canonical: "/about" } };

export default function AboutPage() {
  return (
    <div className="prose-paper mx-auto max-w-3xl">
      <p className="eyebrow" style={{ fontFamily: "var(--font-sans)" }}>
        About
      </p>
      <h1>AutoScholar.ai</h1>
      <p>
        AutoScholar is a research-producing startup and a public library of original working papers produced
        by an autonomous, auditable AI research workflow. The product is not a chatbot, an essay generator or
        a subscription for spun articles. It is a steadily growing body of research whose every release
        carries its own evidence.
      </p>
      <h2>What we are</h2>
      <p>
        A one-person founder operation with an automated research pipeline. A single administrator writes
        research instructions, launches runs on our compute infrastructure, and the platform plans,
        investigates the literature, executes analyses or proofs, writes a LaTeX manuscript, subjects it to an
        independent automated critical review, rebuilds and verifies the result, and publishes it only when
        deterministic quality gates pass.
      </p>
      <h2>What we are not</h2>
      <ul>
        <li>
          We are not a journal. AutoScholar working papers are preprints; they are{" "}
          <strong>not peer reviewed</strong> by humans.
        </li>
        <li>
          We do not have an editorial board, invented authors or academic affiliations. The byline of every
          paper is “AutoScholar — AI-generated research”.
        </li>
        <li>We do not register DOIs. Papers are identified by stable AutoScholar working-paper numbers.</li>
        <li>We do not report view counts, citation counts or ratings that we cannot verify.</li>
      </ul>
      <h2>Automation disclosure</h2>
      <p>
        Research planning, source retrieval, code, analysis, writing and automated review are performed by
        large language models (Claude, via the Anthropic API) orchestrated by platform software with enforced
        permissions and budgets. Humans set the research questions, configure policies, review gate outcomes,
        and can correct or retract any paper. See the <Link href="/methodology">methodology</Link> and{" "}
        <Link href="/transparency">transparency</Link> pages.
      </p>
      <h2>Infrastructure</h2>
      <p>
        Research is computed on MacLustr, an Apple Silicon research compute infrastructure. See{" "}
        <Link href="/infrastructure">Powered by MacLustr</Link>.
      </p>
    </div>
  );
}