ResearchVerify

When more than one lab tests the same batch, we line up their results side by side. When they match, it is the strongest signal you can get. When they do not, that is information too. Here is what these labs found — you decide.

3 independent labs tested this batch of CJC-1295 (no-DAC) from Astro Peptides. Their purity results ranged from 56% to 92%.
The labs do NOT agree

That is a wide spread. When labs disagree this much on the same batch, no single certificate tells the whole story.

On the actual amount per vial, the labs were far apart (2.4 to 4.5 mg).

Heads up: our overall RV score may read these labs as close. That is because the score blends purity with other factors and compresses big differences. When you weigh this batch, the raw purity range above is what matters, not the smoothed score.

✓ Multi-Lab Verified · Poor · 4.3

The two badges above are our blended RV-score view: whether the scores agree, and the overall quality tier. The plain read at the top leads with the labs actual purity numbers, and the full per-lab table is below.

CJC-1295 (no-DAC) from Astro Peptides
batch CJC5-13596 · 5 independent measurements across 3 labs (after collapsing same-test duplicates)

Independent labs agree on this batch within 0.5 RV-score points. Strong cross-validation.

✓ Batch identity basis: Same physical sample (Finnrick multi-lab program)
All records carry Finnrick (FNR-*) task IDs, meaning one physical vial was routed by Finnrick to multiple labs and each lab tested it independently. This is the strongest basis for 'same batch' — there's no batch heterogeneity between labs because there's no batch difference: it's the same vial.
⚠ Same-test duplicates detected (2 records in 1 cluster). Some rows share identical measurement tuples (content + purity + date) — these appear to be one test counted multiple times, not independent measurements. They're flagged "SAME TEST" in the table below and collapsed to one vote for the cross-lab agreement math. Cross-lab corroboration requires actually-independent tests.
🧞 Identity caveat — Distinct molecule from CJC-1295 DAC (DAC adds Drug Affinity Complex → days-long half-life). Bare 'CJC-1295' resolves here per peptide-research market convention: ≥99% of bare-term COAs are no-DAC (Mod GRF 1-29). Vendors advertising DAC form state so explicitly. If a record's DAC/no-DAC matters for downstream analysis, verify against the COA notes — do not blindly trust this resolution.
Reporting-basis mismatch or different denominator — investigate. One lab's measurement is more than 1.8× another's. Counterion plus residual water tops out around 1.3–1.5× even in bad cases, so a spread this large usually means the two labs aren't measuring the same thing — different denominator (per-mL vs per-vial), a dilution-factor mismatch, a decimal slip, or a sample-prep difference. The compound itself may be fine; the disagreement is about how it was quantified. Resolves once method/basis is surfaced per lab.
Same method, results still diverge — investigate. All labs reported HPLC but results diverge — batch heterogeneity, calibration drift, or sample handling worth investigating. When labs share the analytical approach but the numbers don't line up, the divergence is doing real work and deserves a closer look.
Labs
3
Tests
6
RV Score Mean
4.32
RV Score Spread
0.45
Content Mean
3.9 mg
⇄ Basis mismatch
Content Range
2.4–4.5 mg
CV 18.1%

Per-Lab Breakdown

All rows (Purity & Content vary, everything else constant): Testing 0.4 · Custody 4.3 · CI 9.0 · Method HPLC
LabTaskTest DateRVPurityContentTestingLabelCustodyCIMethod
Freedom DiagnosticsSAME TEST#FNR-lcg6j6c4.4788.48%4.5 mg0.48.54.39.0HPLC
Freedom DiagnosticsSAME TEST#FNR-cm9tbpz4.4788.48%4.5 mg0.48.54.39.0HPLC
Janoshik#FNR-snydbv34.0256.00%2.4 mg0.47.04.39.0HPLC
Janoshik#FNR-pabtlbw4.4792.00%4.0 mg0.48.54.39.0HPLC
MZ Biolabs#FNR-6t6sw4f4.4789.00%4.2 mg0.48.54.39.0HPLC
MZ Biolabs#FNR-wlfrqxi4.0285.70%3.9 mg0.47.04.39.0HPLC
Why this matters: A single COA is one lab's answer from one method on one sample. Multiple labs reveal the pattern. When labs converge on the same answer, that's strong cross-validation. When they diverge — especially on content while agreeing on purity — the difference is often method-driven (different quantitation basis) but sometimes signals real product variation. ResearchVerify is the only platform that surfaces both cases automatically across thousands of cross-tests.