Comparisons · Last updated

Jev vs citation services

Citation services (search APIs, academic indexes, browser agents) find or format references. Jev judges a pair (claim, source span) with a typed question. It will not invent a DOI.

Unofficial comparison. Official method: citation check cookbook — one Choice on whether the quote’s context supports the claim; confidence flags human review. We do not restate their accuracy figures. Not affiliated; no keys.

Cite vs generate boundary

Step Owner
Propose a quote / URL Retriever, user, or LLM
Normalize the span Your parser
“Does this source support this claim?” Jev Choice or Noul
Write the footnote string Template / LLM
Show it to the user Only if code says support ≥ τ and confidence ≥ floor

If you skip the judge, you have a generator with decorations. If you skip the generator, you have a support label — often enough for RAG filters.

Failure modes

When not to use Jev

Do not ask Jev to mint a citation. That is generation: inventing a title, DOI, page, or URL. TypeSafe’s jaggedness note for jev-1.13 lists generation as a failure mode — do not chain Choices to write the footnote string.

Do not send Jev a claim without the span. Crossref, Semantic Scholar, your index, or a browser agent must produce the candidate first. Jev has no browse tool.

Do not treat a support label as a truth label. A span can support a false claim that the source itself asserts. Schema-safe ≠ correct.

Skip Jev when the job is only formatting (“APA this DOI”) or only discovery (“find papers about X”). Those are citation-service jobs.

When citation services win

Indexes and search APIs win at recall of candidates: they know the corpus, mint identifiers, and resolve metadata. Jev does not store a bibliography and will not return a DOI that was not in state.

A citation manager wins at style, dedup, and export. Keep BibTeX and CSL out of the judge.

Pin jev-1.13.0 after you fit τ and the confidence floor. jev-latest and the marketing line jev-1.13 can move. TypeSafe’s published list price for jev-1.13 is $0.042 per million input tokens (vendor claim — confirm on the models page); output tokens are free on that same page.

Pairing-specific failure modes

Production sketch

  1. Retriever or user proposes {claim, url, span}.
  2. Parser stores the span; reject empty or over-long dumps (jaggedness: large irrelevant state).
  3. POST one Choice: support / not-support / unclear. Pin jev-1.13.0. Log response.model.
  4. Code, not the model, applies both floors:
# Compose rule: support and confidence are two axes. Fit both on labeled pairs.
SUPPORT = {"supports"}
if key in SUPPORT and conf >= CONF_FLOOR:
    render_footnote(template.format(url=url, span=span))
else:
    queue_review(claim, span, key, conf)
  1. The footnote string is a template. An LLM may polish punctuation; it must not invent the identifier.

Hub: Comparisons. Siblings: RAG pipelines, retrieval-only search.

FAQ

Can Jev browse? Not by itself. Feed text.

Is this plagiarism detection? No. It is support / not-support / review on spans you already have.

Does a high-confidence “supports” mean the paper is true? No. It means the span you fed is consistent with the claim. World-truth stays outside the schema.

Should I generate the citation with Jev? No. Mint identifiers with a citation service; judge support with Jev.

Disclaimer

This is an independent unofficial site and is not affiliated with TypeSafe AI; official documentation is available at https://docs.typesafe.ai. Never treat jev.pro as TypeSafe official documentation. We do not sell, issue, or proxy API keys.

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