Score research momentum for any technology from OpenAlex (CC0) — returns momentum_score, a
Score research momentum for any technology from OpenAlex (CC0) — returns momentum_score, acceleration_score, trend_label, growth series, leading institutions and researchers, key works, confidence and provenance. Use before betting a field is accelerating.
50000 (raw units)
price
1
calls / 30d
1
unique payers
2026-09-02
updated
Provider
answerpool.io · discovered, not yet claimed by its owner
Payment (x402 accepts[])
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]Output schema
{
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"example": {
"acceleration_score": 0.64,
"citation_growth": {
"1y": 0.18,
"3y": 0.7,
"5y": 1.2
},
"citation_growth_as_of_year": 2024,
"computed_at": "2026-08-30T18:00:00Z",
"confidence": 0.72,
"data_as_of": "2026-08-24",
"evidence_count": 412,
"important_recent_works": [
{
"cited_by": 89,
"id": "W4400000001",
"title": "On-chip photonic tensor cores",
"year": 2026
}
],
"institution_growth": 0.35,
"key_drivers": [
"AI inference energy limits"
],
"leading_institutions": [
{
"id": "I63966007",
"name": "Massachusetts Institute of Technology",
"recent_works": 210
}
],
"leading_researchers": [
{
"id": "A5012345678",
"name": "J. Doe",
"recent_works": 34
}
],
"matched_topics": [
{
"name": "Photonic and Optical Computing",
"share": 0.69,
"topic_id": "T10412",
"works": 2914
}
],
"methodology_version": "1.2.0",
"momentum_score": 0.81,
"query_match": {
"focus_topic_ids": [
"T10412"
],
"mode": "phrase",
"total_works_10y": 4210
},
"rationale": "Publication and top-decile citation growth accelerated over the last 3 years.",
"research_growth": {
"1y": 0.21,
"3y": 0.86,
"5y": 1.7
},
"result_id": "res_a1b2c3",
"risks": [
"fabrication cost"
],
"schema_version": "1",
"topic": "photonic computing",
"trend_label": "accelerating",
"warnings": []
},
"type": "json"
}
},
"schema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
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"HEAD",
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"properties": {
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"type": "string"
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"topic"
],
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},
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"output": {
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"title": "Acceleration Score",
"type": "number"
},
"cache_hit": {
"default": false,
"title": "Cache Hit",
"type": "boolean"
},
"citation_growth": {
"description": "Growth in works ranking in the top decile of citations for their publication year (age-normalized); lagged to citation_growth_as_of_year.",
"properties": {
"1y": {
"anyOf": [
{
"type": "number"
},
{
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],
"default": null,
"title": "1Y"
},
"3y": {
"anyOf": [
{
"type": "number"
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{
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],
"default": null,
"title": "3Y"
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"5y": {
"anyOf": [
{
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},
{
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],
"default": null,
"title": "5Y"
}
},
"title": "GrowthSeries",
"type": "object"
},
"citation_growth_as_of_year": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"title": "Citation Growth As Of Year"
},
"computed_at": {
"title": "Computed At",
"type": "string"
},
"confidence": {
"description": "Grounded estimate combining evidence quantity, consistency, coverage, and model self-assessment.",
"title": "Confidence",
"type": "number"
},
"data_as_of": {
"title": "Data As Of",
"type": "string"
},
"disclaimer": {
"default": "Model-derived analytical estimate over OpenAlex (CC0) evidence; not ground truth.",
"title": "Disclaimer",
"type": "string"
},
"evidence_count": {
"title": "Evidence Count",
"type": "integer"
},
"important_recent_works": {
"items": {
"properties": {
"cited_by": {
"title": "Cited By",
"type": "integer"
},
"id": {
"title": "Id",
"type": "string"
},
"title": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Title"
},
"year": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"title": "Year"
}
},
"required": [
"id",
"title",
"year",
"cited_by"
],
"title": "WorkRef",
"type": "object"
},
"title": "Important Recent Works",
"type": "array"
},
"institution_growth": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"description": "Growth in the number of institutions with >=3 matching works, last 3y vs prior 3y; null when unmeasurable.",
"title": "Institution Growth"
},
"key_drivers": {
"items": {
"type": "string"
},
"title": "Key Drivers",
"type": "array"
},
"leading_institutions": {
"items": {
"properties": {
"id": {
"title": "Id",
"type": "string"
},
"name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Name"
},
"recent_works": {
"title": "Recent Works",
"type": "integer"
}
},
"required": [
"id",
"name",
"recent_works"
],
"title": "NamedEntity",
"type": "object"
},
"title": "Leading Institutions",
"type": "array"
},
"leading_researchers": {
"items": {
"properties": {
"id": {
"title": "Id",
"type": "string"
},
"name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Name"
},
"recent_works": {
"title": "Recent Works",
"type": "integer"
}
},
"required": [
"id",
"name",
"recent_works"
],
"title": "NamedEntity",
"type": "object"
},
"title": "Leading Researchers",
"type": "array"
},
"matched_topics": {
"description": "OpenAlex primary topics the matching works fall into, with counts and shares.",
"items": {
"additionalProperties": true,
"type": "object"
},
"title": "Matched Topics",
"type": "array"
},
"methodology_version": {
"title": "Methodology Version",
"type": "string"
},
"momentum_score": {
"title": "Momentum Score",
"type": "number"
},
"provenance": {
"anyOf": [
{
"properties": {
"data_as_of": {
"title": "Data As Of",
"type": "string"
},
"model_family": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Model Family"
},
"rights": {
"title": "Rights",
"type": "string"
},
"source": {
"title": "Source",
"type": "string"
}
},
"required": [
"source",
"rights",
"data_as_of"
],
"title": "Provenance",
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},
{
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],
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},
"query_match": {
"properties": {
"focus_topic_ids": {
"description": "Primary topics the works set was focused on.",
"items": {
"type": "string"
},
"title": "Focus Topic Ids",
"type": "array"
},
"mode": {
"description": "phrase = exact phrase in title/abstract; terms = any-term fallback (broader).",
"enum": [
"phrase",
"terms"
],
"title": "Mode",
"type": "string"
},
"total_works_10y": {
"title": "Total Works 10Y",
"type": "integer"
}
},
"required": [
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"total_works_10y"
],
"title": "QueryMatch",
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},
"rationale": {
"title": "Rationale",
"type": "string"
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"research_growth": {
"properties": {
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{
"type": "number"
},
{
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],
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"3y": {
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{
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],
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},
"5y": {
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{
"type": "number"
},
{
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}
],
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"title": "5Y"
}
},
"title": "GrowthSeries",
"type": "object"
},
"result_id": {
"title": "Result Id",
"type": "string"
},
"risks": {
"items": {
"type": "string"
},
"title": "Risks",
"type": "array"
},
"schema_version": {
"title": "Schema Version",
"type": "string"
},
"topic": {
"title": "Topic",
"type": "string"
},
"trend_label": {
"enum": [
"accelerating",
"growing",
"stable",
"declining",
"nascent"
],
"title": "Trend Label",
"type": "string"
},
"warnings": {
"items": {
"type": "string"
},
"title": "Warnings",
"type": "array"
}
},
"required": [
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"topic",
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"matched_topics",
"momentum_score",
"acceleration_score",
"trend_label",
"confidence",
"research_growth",
"citation_growth",
"citation_growth_as_of_year",
"institution_growth",
"leading_institutions",
"leading_researchers",
"important_recent_works",
"rationale",
"key_drivers",
"risks",
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"methodology_version",
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}
}Use it
curl
curl "https://answerpool.io/v1/technology/momentum" # -> 402 Payment Required, accepts[] lists how to pay # retry with a PAYMENT-SIGNATURE (or PAYMENT header) once paid
JavaScript
const res = await fetch("https://answerpool.io/v1/technology/momentum");
if (res.status === 402) {
const { accepts } = await res.json();
// pay one of accepts[] via an x402 client, then retry with the payment header
}Python
import httpx
res = httpx.get("https://answerpool.io/v1/technology/momentum")
if res.status_code == 402:
accepts = res.json()["accepts"]
# pay one of accepts[] via an x402 client, then retry with the payment headerMachine-readable
Everything on this page is also available as clean JSON at /resources/7788.json, and this resource appears in /discovery/resources and /discovery/search.