Verified claim · AI-ML · 100% confidence
AlphaFold 2 published in paper: Highly accurate protein structure prediction with AlphaFold (Jumper et al., 2021).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 477bc19212addf9a
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Structured fields
- Subject
- AlphaFold 2
- Predicate
published_in_paper- Object
- Highly accurate protein structure prediction with AlphaFold (Jumper et al., 2021)
- Confidence
- 100%
- Tags
- alphafold · deepmind · biology · 2021 · nature · protein
Sources (2)
[1] peer reviewed · Nature (Jumper et al., DeepMind) · 2021-07-15
Highly accurate protein structure prediction with AlphaFold“Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even where no similar structure is known.”
[2] official blog · DeepMind · 2020-11-30
AlphaFold: a solution to a 50-year-old grand challenge in biology
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Frequently asked questions
Is the claim "AlphaFold 2 published in paper: Highly accurate protein structure prediction with AlphaFold (Jumper et al., 2021)." verified?
Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: Nature (Jumper et al., DeepMind), DeepMind. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/477bc19212addf9a.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
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const r = await fetch("https://sourcescore.org/api/v1/claims/477bc19212addf9a.json");
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// "AlphaFold 2 published in paper: Highly accurate protein structure prediction with AlphaFold (Jumper et al., 2021)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/477bc19212addf9a.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "AlphaFold 2 published in paper: Highly accurate protein structure prediction with AlphaFold (Jumper et al., 2021)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_alphafold_2_fact() -> dict:
"""Fetch the verified SourceScore claim for AlphaFold 2."""
r = httpx.get("https://sourcescore.org/api/v1/claims/477bc19212addf9a.json")
return r.json()