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Interpretation · Base / 8453

What does data quality mean in a token risk scan?

Separate evidence completeness from risk severity

Direct answer

Data quality describes how complete and reliable the available evidence is; it is not the same as the token's risk level. A token can have low measured risk but incomplete evidence, which should reduce confidence rather than be translated into a clean bill of health.

Risk and evidence are different axes

Risk fields ask what the available data says about the token. Data-quality fields ask how much usable evidence was available to support that conclusion.

Combining the two prevents a common failure mode: interpreting missing fields as zero risk.

Jepeta fail-closed boundary

Jepeta requires GoPlus coverage and explicit honeypot/mintability values for a successful strict preview. Required unknowns do not become false.

DEX Screener market context can be partial or unavailable; Jepeta surfaces that source status separately and keeps unavailable market values null.

Why permanent pages require a quality gate

T037 only promotes already-published tokens with HIGH or MEDIUM public data quality, explicit security booleans, and at least two non-null public evidence dimensions.

This means ordinary or low-quality scans do not become indexable SEO pages, reducing both misinformation risk and thin-content risk. It also keeps citations and search snippets tied to evidence that is complete enough to explain responsibly.

Practical checklist

  • Read data quality separately from risk level
  • Inspect source status
  • Keep null distinct from zero
  • Require explicit critical booleans
  • Prefer fresh evidence

Limitations

This is educational risk-screening content, not investment advice. Token and market conditions can change after any snapshot. A PASS result or negative honeypot signal is not a safety guarantee.