Reference  ·  Trust Grade rubric

How we grade vendors.

A Trust Grade is a deterministic summary of what third-party labs, community forums, and Discord-uploaded certificates have said about a vendor. This page lists every input, every formula, every cutoff — and how a vendor can dispute a result.

Version 1.0Effective 2026-04-21Public — no login required

Every graded vendor gets a single score on a 0–100 scale — a weighted sum of six components, each anchored in measured lab or community data. Letter grades (A+ through F) are assigned by comparing each vendor's score against the distribution of all graded vendors: calibrated quantiles, not fixed cutoffs.

Vendors below the evidence floor (fewer than three lab tests or fewer than ten community posts) are not graded at all; they display as insufficient data. A score below the 5th percentile receives an F. Everything in between follows the quantile ladder in §04.

Weights are defined in scripts/coa/trust_stats.py (constant WEIGHTS) and sum to 1.00. Any change bumps the methodology version (§09).

Bar length is proportional to weight; the 30% bar saturates the row. Sum = 100%.

Each component produces a 0–100 sub-score after empirical-Bayes shrinkage (§05) and 180-day-half-life recency weighting — today counts 1.0, six months 0.5, four years is floored at 0.05.

3.1

Assay purity

Weight 30%

Weighted-mean HPLC purity across every lab test attributed to the vendor, scored on a piecewise- linear curve anchored at industry-realistic breakpoints (99.5% → 95, 99.0% → 85, 98.0% → 65).

Formula

score_purity(p) — piecewise-linear, monotone: p ≥ 99.5 → 95 + 10·(p − 99.5) [cap 100] p ≥ 99.0 → 85 + 20·(p − 99.0) p ≥ 98.0 → 65 + 20·(p − 98.0) p ≥ 95.0 → 25 + 40/3·(p − 95.0) p < 95.0 → 5 + 4·(p − 90.0), floored 0

Data source

coa_records rows with the purity column populated (Janoshik, Finnrick, Discord/Telegram uploads, glp1forum attachments).

Adjustments

Simpson's-paradox correction per peptide — vendors running easier-to-synthesize peptides do not get free credit over vendors running harder ones.

Insufficient data

Fewer than three tests: vendor is not graded.

3.2

Quantity accuracy

Weight 25%

How close the measured peptide mass is to the labeled mass. A vial labeled 10 mg that assays at 9.3 mg has a −7-point deviation. Over- and under-dose are scored symmetrically on a smooth exponential curve.

Formula

score_qty_dev(d) = 100 · exp(−|d| / 7) d = 0 → 100 d = 7 → 36.8 d = 15 → 11.7 d = 50 → 0.08

Data source

quantity_deviation_pct column of coa_records, populated from lab reports that include a measured mass or concentration.

Insufficient data

Tests without a measured quantity are skipped; vendors with none fall back to the shrunk population mean rather than scoring zero.

3.3

Public verification

Weight 15%

Count of independent public lab tests — Janoshik and Finnrick results on their own sites, not vendor-uploaded PDFs. Rewards breadth: five already score substantially above zero, 25 approaches the ceiling.

Formula

score_public(n) = 100 · (1 − exp(−n / 8)) n = 0 → 0 n = 8 → 63.2 n = 11 → 75 n = 25 → 95.6

Data source

Count of coa_records rows with source IN ('janoshik_public', 'finnrick').

Edge case

Does not replace the full grade — a vendor with 50 public tests but a 91% mean purity still scores poorly on §3.1.

3.4

Batch consistency

Weight 12%

Pooled standard deviation of purity across peptides and batches. Tight clusters — purity within half a percentage point batch-to-batch — score at the top. Dispersed results signal process variance regardless of mean.

Formula

score_consistency(σ) = 100 · exp(−σ / 0.7) σ = 0.0 → 100 σ = 0.7 → 36.8 σ = 1.5 → 11.7 σ = 5.0 → 0.08

Data source

Computed across vendor × peptide cells of coa_records with Bessel correction.

Insufficient data

Single-test peptides contribute zero to pooled SD; the consistency score falls back to the shrunk population mean.

3.5

Endotoxin pass rate

Weight 10%

Endotoxin (LAL / bacterial contamination) pass rate as a Beta-Binomial posterior mean. Vendors with no endotoxin-bearing tests score at the prior mean (80); each pass pulls up, each fail pulls sharply down.

Formula

score_endotoxin(pass, fail) = 100 · (α + pass) / (α + β + pass + fail) prior: α=8, β=2 (prior mean 80) (0, 0) → 80 (5, 0) → 86.7 (20, 0) → 93.3 (18, 2) → 86.7

Data source

endotoxins_status column of coa_records. Pass tokens: below loq, not detected, <LOQ, pass, negative, ND, undetected. Any other non-null value is a fail.

Edge case

One fail in 20 tests drops the score ~7 points; one fail in 3 tests drops it ~18. Sample size is accounted for automatically by the posterior.

3.6

Evidence weight

Weight 8%

Proxy for the breadth and recency of the evidence base. Uses the recency-weighted effective sample size — not the raw test count — so 30 tests from two years ago do not score the same as 30 from the last six months. Separates "deep evidence base" from "good vendor."

Formula

score_evidence(n_eff) = 100 · (1 − exp(−n_eff / 10)) n_eff = 0 → 0 n_eff = 10 → 63.2 n_eff = 20 → 86.5 n_eff = 30 → 95.0

Data source

Sum of per-record recency weights (see §05) across all coa_records for the vendor.

Letter grades use quantile cutoffs over the full graded population, refreshed and cached every 15 minutes. When the population drops below 20 vendors we fall back to fixed cutoffs (shown below) to prevent pathological scaling on small samples.

Letter	Label	Population cutoff	Fallback score (<20 vendors)
A+	Elite	≥ p95	≥ 92.0
A	Trusted	p80 – p95	88.0 – 92.0
B+	Strong	p60 – p80	82.0 – 88.0
B	Solid	p40 – p60	76.0 – 82.0
C	Mixed	p20 – p40	68.0 – 76.0
D	Caution	p5 – p20	55.0 – 68.0
F	Avoid	< p5	< 55.0

Example: if the 95th-percentile composite is 89.4, every vendor at or above 89.4 receives an A+; anyone below the 5th percentile receives an F, however low that happens to be.

Two adjustments apply before components are assembled. Both are conservative: they pull small-sample estimates toward the population mean and discount older tests, so thin or stale data cannot rocket a vendor to the top on a single favourable batch.

Empirical-Bayes shrinkage. The observed vendor mean is blended with the population mean as (n · x̄ + k · μ) / (n + k), with per-component k — purity 5, qty_dev 5, consistency 3, endotoxin 4. One test ≈ 17% vendor / 83% population; 25 tests ≈ 83% vendor / 17% population.

Recency weighting. Each record is multiplied by 0.5 ^ (age_days / 180), floored at 0.05. A record with no parseable date gets weight 0.5.

Thin evidence is reported as insufficient data rather than as a low grade. Rules are enforced at the query layer, not hidden in score arithmetic:

• Fewer than three lab tests in coa_records → no grade, no composite score; vendor tagged "insufficient data."
• Fewer than ten forum posts across glp1forum and Discord → community-signal components are suppressed on the dossier.
• Umbrella manufacturers (one factory, multiple resale brands) are graded at the factory level; resale brands link back, not double-counted.
• Zero records in the last 18 months → marked dormant. Grade freezes at last computation and shows a staleness badge.

Every input is sourced from one of four public or community-mediated channels. We do not commission tests, accept vendor-paid data, or take vendor submissions without a provenance field.

Every coa_records row carries an immutable source field and a source_url whenever one exists. Vendor dossiers expose the raw records behind any grade under /v/<slug>, so a reader can audit inputs without trusting our aggregation.

Any vendor — graded, insufficient-data, or dormant — may contest the data behind a grade. We accept three categories of dispute with defined SLAs:

1. Misattribution. A COA or forum post linked to the wrong vendor. SLA: 72 hours to correct or confirm; correction is retroactive and re-triggers grade computation.
2. Retracted or superseded test. A lab has retracted, amended, or re-issued a COA we still show as canonical. SLA: 5 business days; original kept for audit with a retraction note, excluded from scoring.
3. Factual error in a scraped post. A forum quote is materially mis-transcribed. SLA: 5 business days; correction note posted alongside the original, source URL cited.

Send disputes to methodology@peptideintel.example with the vendor name, record ID or URL, and nature of the correction. Disputes are logged and the log is available on request. We do not remove records for reputational reasons — only for factual ones.

Changes to weights, formulas, cutoffs, or data-source handling bump the version and are listed here. Historical grades remain viewable under their as-of version via the dossier's grade-history panel.