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CortexAssay Technology Momentum
x402
CortexAssay Technology Momentum is a paid API for AI agents from cortexassay.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).
Computes a momentum score and trend analysis for a given technology topic using academic publication and citation growth data from OpenAlex.
Price / call$0.05
Success—
StatusUnknown
How this service works
Machine-consumable research and technology intelligence computed from open data (OpenAlex, CC0). Pay per call with x402. Schemas, prices and provenance are machine-readable.
Output
Returns a JSON object containing a momentum_score (0–1), trend_label (e.g. 'accelerating'), acceleration_score, confidence, citation_growth rates (1y/3y/5y), research_growth rates, institution_growth, matched academic topics with share and work counts, leading researchers and institutions, important recent works, key drivers, risks, warnings, rationale text, and data provenance fields (data_as_of, computed_at, methodology_version).
Example use cases
Emerging technology investment screening
“I'm evaluating whether to fund a startup in neuromorphic computing — can you pull the technology momentum score for neuromorphic chips and tell me if research output and citations are accelerating or stalling?”
Competitive landscape research briefing
“Give me the academic momentum score and trend label for solid-state battery technology, including citation growth over the last 3 years and which institutions are leading the research.”
Technology roadmap horizon scanning
“I'm building a 5-year roadmap and want to know if quantum error correction is genuinely accelerating in research output — pull the momentum score, acceleration score, and key drivers for that topic.”
Technical details
Endpoint
GEThttps://cortexassay.com/v1/technology/momentumWhen to prefer
Choose this endpoint when you need a quantitative, evidence-grounded momentum signal for a specific technology domain derived from peer-reviewed literature — especially when you need citation growth rates, institutional leaders, and a machine-readable confidence score rather than subjective analyst opinion. Prefer this over general web search when you need reproducible, provenance-tracked research intelligence. Best suited for technology due diligence, innovation scouting, and research roadmap decisions.
Side effects
- Topic query matches no known OpenAlex topics — returns empty matched_topics or low confidence
- Ambiguous topic string matches multiple unrelated fields — check query_match.mode and matched_topics shares
- Insufficient publication volume for reliable scoring — evidence_count may be low with high uncertainty
- Payment failure via x402 — 402 response if USDC payment not completed
- Rate limiting or service unavailability — 429 or 5xx responses
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| required | string | |
| properties | string |
Output
Schema · Response
{
"type": "json",
"example": {
"risks": [
"fabrication cost"
],
"topic": "photonic computing",
"warnings": [],
"rationale": "Publication and top-decile citation growth accelerated over the last 3 years.",
"result_id": "res_a1b2c3",
"confidence": 0.72,
"data_as_of": "2026-08-24",
"computed_at": "2026-08-30T18:00:00Z",
"key_drivers": [
"AI inference energy limits"
],
"query_match": {
"mode": "phrase",
"focus_topic_ids": [
"T10412"
],
"total_works_10y": 4210
},
"trend_label": "accelerating",
"evidence_count": 412,
"matched_topics": [
{
"name": "Photonic and Optical Computing",
"share": 0.69,
"works": 2914,
"topic_id": "T10412"
}
],
"momentum_score": 0.81,
"schema_version": "1",
"citation_growth": {
"1y": 0.18,
"3y": 0.7,
"5y": 1.2
},
"research_growth": {
"1y": 0.21,
"3y": 0.86,
"5y": 1.7
},
"acceleration_score": 0.64,
"institution_growth": 0.35,
"leading_researchers": [
{
"id": "A5012345678",
"name": "J. Doe",
"recent_works": 34
}
],
"methodology_version": "1.2.0",
"leading_institutions": [
{
"id": "I63966007",
"name": "Massachusetts Institute of Technology",
"recent_works": 210
}
],
"important_recent_works": [
{
"id": "W4400000001",
"year": 2026,
"title": "On-chip photonic tensor cores",
"cited_by": 89
}
],
"citation_growth_as_of_year": 2024
}
}Tags
x402
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