Jev Research Evidence Sorter

Rank supplied research snippets by relevance to your question and by the kind of evidence they actually are, while keeping every source URL attached.

It is part of the Jev family: narrow, typed judgements on records you supply, with the code owning everything deterministic and the model owning only the judgement. Bring a TypeSafe API key as a secret input for live judgements.

What it does

• Scores each snippet's relevance to your question.
• Classifies the evidence type.
• Preserves the source URL on every row so nothing is detached from its origin.
• Keeps your sourceId.

What it does not do

Scoping this honestly is the point of the family, so it is stated plainly:

• It does not search the web or fetch pages.
• It does not summarise into prose you could mistake for a source.
• It does not invent citations.

Output fields

Field	Description
index	Position of this row within the run.
sourceId	Your identifier for the snippet.
url	The source URL, preserved as supplied.
text	The snippet text that was judged.
relevance	How relevant the snippet is to the question.
evidenceType	The kind of evidence the snippet represents.
judgments	The full structured judgement.
model	Identifier of the model used.

Sample output

{
  "index": 1,
  "sourceId": "src_31",
  "url": "https://example.org/study",
  "text": "A 2024 trial found no effect.",
  "relevance": "high",
  "evidenceType": "primary study",
  "judgments": {
    "relevance": {
      "choice": "high"
    }
  },
  "model": "jev-latest"
}

How it works

Each supplied record is turned into a question set and sent to the TypeSafe Jev model, which answers with a choice, a score, or a probability. Those answers are mapped onto fixed output fields, and every row carries the confidence of the judgements behind it.

status reports the outcome per row. When the minimum confidence falls below your threshold, or the model's own uncertainty is high, the row is flagged for review rather than presented as a settled answer. minConfidence records the weakest judgement that produced the row, so you can see how close it was.

Safe mode. With no TypeSafe key the Actor sends nothing upstream and returns a single row with status: "no_api_key" — a successful run that tells you exactly what to add, never a failed one.

Pricing

Pay per event: you are charged per result written to the dataset, plus the near-zero start event. In safe mode no judgements are produced, so the run is effectively free. Bring your own TypeSafe key; you pay TypeSafe separately for the model calls.

FAQ

Does it need a TypeSafe key? For real judgements, yes — add it as a secret input. Without one it runs in safe mode and returns no_api_key instead of guessing.

Does it call any other service? No. It reads your supplied records and calls the Jev model. It does not fetch, scrape, crawl or contact anything.

What does review mean? The judgement was not confident enough to stand on its own. Treat those rows as needing a human, not as answers.

Can I tune the threshold? Yes. Raise the confidence threshold to get fewer, more certain results; lower it to see more rows with more of them flagged for review.

Is the output deterministic? The mapping and the fields are fixed. The model's judgement is probabilistic, which is why every row carries a confidence and why low-confidence rows are flagged rather than hidden.

Use cases

• Sorting a literature pile before reading it.
• Separating primary evidence from commentary.
• Keeping provenance attached through an AI-assisted review.

Related Actors

• Jev AEO GEO Visibility Enricher
• Docs to Answers

What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in an answer or a comparison.

• Jev Research Evidence Sorter declares all 8 of its output fields in its dataset schema, each with a type, a written description and an example value.
• The output fields of Jev Research Evidence Sorter include index, sourceId, url, text, relevance and evidenceType.
• Jev Research Evidence Sorter needs no API key, login or account of any kind before its first run.
• Every one of Jev Research Evidence Sorter's 4 inputs is optional, so it runs with no configuration at all.
• Jev Research Evidence Sorter documents sourceId as: Identifier of the input record this row came from.
• Every number published about Jev Research Evidence Sorter is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
• Jev Research Evidence Sorter is filed under ai and business so that it is found by the people looking for that job, not by its internal name.

Limitations

• Jev Research Evidence Sorter reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
• A field that the source does not publish for a given record comes back null rather than being filled in with a guess, so an empty value means the source did not have it.
• Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
• This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.