Science Topics API: 4,500-topic research directory with weekly-computed growth and momentum — OpenAlex
4,500-topic research directory with weekly-computed growth and momentum stats: search by name or field, sort by momentum, works or growth. Raw numbers, no LLM. Free, no key.
Free — no key, no signup, rate-limited to 60 calls per minute per client.
How do you call it?
GET /v1/science/topics — product id
science_topics. Over MCP, call answerpool_get with
product_id=science_topics.
curl "https://answerpool.io/v1/science/topics?q=quantum"Live call: https://answerpool.io/v1/science/topics?q=quantum · JSON sample: /v1/samples/science_topics
What does the answer look like?
A representative response, the same static sample served at /v1/samples/science_topics.
as_of | 2026-09-03T02:00:00Z |
|---|---|
data_as_of | 2026-08-30 |
count | 1 |
note | Raw weekly-scan statistics; the LLM-graded brief is /v1/technology/emerging. |
disclaimer | Derived from OpenAlex (CC0) by AnswerPool's weekly scan; not investment advice. |
refresh_after | 2026-09-18T00:00:00.000Z |
topics
| topic_id | name | field | subfield | works_last_full_year | works_10y | growth_1y | growth_3y | momentum_rank | is_emerging |
|---|---|---|---|---|---|---|---|---|---|
| T10320 | Quantum Computing Algorithms and Architecture | Computer Science | Computational Theory and Mathematics | 3175 | 18402 | 0.18 | 0.52 | 14 | true |
The same sample as raw JSON
{
"as_of": "2026-09-03T02:00:00Z",
"data_as_of": "2026-08-30",
"count": 1,
"topics": [
{
"topic_id": "T10320",
"name": "Quantum Computing Algorithms and Architecture",
"field": "Computer Science",
"subfield": "Computational Theory and Mathematics",
"works_last_full_year": 3175,
"works_10y": 18402,
"growth_1y": 0.18,
"growth_3y": 0.52,
"momentum_rank": 14,
"is_emerging": true
}
],
"note": "Raw weekly-scan statistics; the LLM-graded brief is /v1/technology/emerging.",
"disclaimer": "Derived from OpenAlex (CC0) by AnswerPool's weekly scan; not investment advice.",
"refresh_after": "2026-09-18T00:00:00.000Z"
}How fresh is it, and where does the data come from?
The fastest source behind this answer can change daily, so every response carries a refresh_after timestamp — right now it would be 2026-09-18T00:00:00.000Z. Schedule the next call on that value rather than on a guess.
- OpenAlex (CC0) — upstream:
https://api.openalex.org
Method version 0.1.0 ·
serving cache 7 days ·
every response carries a result_id you can resolve at
/v1/provenance.
When should you use it?
You need topic resolution or raw growth numbers for research areas — screening before the graded momentum products.
What you skip building
- OpenAlex topic pagination
- hand-rolled growth math
- inconsistent week-to-week baselines
When should you not use it?
Graded assessments with confidence and evidence — that is /v1/technology/momentum ($0.05, LLM-graded).
Where else can you find this?
- Catalog entry (JSON, free)
- OpenAPI schema — input and output types, prices, the 402 flow
- llms.txt — every product in one plain-text document