Rating layers: the four independent inputs behind every score.
Every NO1GEVITY score is built from four layers of data. Each layer answers a different question, and each is sourced separately. The layers are independent by design: a product can score well on one and poorly on another.
Layer 1: Product verification
Does the capsule contain what the label says, at the dose the label says, free of contaminants?
This layer compares declared content against measured content. It records heavy metals, GMP (good manufacturing practice) status, and whether a batch certificate of analysis is publicly available. A product that passes here has proven it contains its ingredients. It has not proven those ingredients do anything.
Sources: ConsumerLab, Labdoor, USP, NSF. These programs buy products and test them independently of the manufacturer.
The full list of what we check, and how each check feeds the quality transparency, is on the testing page. Independent testing →
Layer 2: Clinical relevance
Is there human evidence for the ingredient, at the dose and duration the product uses?
This layer assigns an evidence grade to each ingredient, then checks the studied dose against the product dose and the study duration against the recommended use period. An ingredient with replicated human randomised controlled trials on relevant endpoints grades A. An ingredient with no credible human evidence grades F. The grade sets the ceiling for that ingredient's contribution to the score.
Sources: PubMed for peer-reviewed trials, ClinicalTrials.gov for registered study protocols and results. We do not cite vendor blogs, affiliate reviews, or marketing pages as evidence.
The exact formula, including how the evidence grade gates the dose score, is published in full. Read the scoring methodology →
Layer 3: Consumer sentiment
What do buyers report about delivery, service, and daily use?
This layer aggregates review sentiment from independent forums, our own platform, and Trustpilot. Where a source has a review volume, we report that volume alongside the sentiment, so a score built on 2,000 reviews is not presented the same as one built on 20.
Sentiment never affects the evidence grade. A product loved by its buyers cannot outrank a better-evidenced product on the back of reviews. Reviews can be farmed, and a high rating is not a clinical outcome.
Consumer sentiment carries a 10% weight in the overall score. That weight is a ceiling, not a floor. It can lift a product a little, but it cannot on its own move a product past a better-evidenced one.
Layer 4: Media and review status
Where has the product been covered, and is that coverage independent?
This layer records placement, methodology, affiliate status, and publication date for any media or review coverage of the product. A review on a site with disclosed methodology and no affiliate links counts differently from a review on a site that earns a commission on every click-through.
Sources: Healthline and niche longevity guides. We record what each source discloses about its own method and its financial relationship to the brand.
A favorable review is not evidence of efficacy. This layer tells you who has covered a product and on what terms. It does not tell you the product works. That question belongs to Layer 2.
How the layers combine
A passed purity test does not prove a longevity effect. Layer 1 can confirm a capsule contains 500 mg of a compound, and Layer 2 can show that compound has no replicated human evidence for the claimed benefit. Both results stand. They answer different questions.
The four layers are independent by design. A product can score well on one and poorly on another. A brand with clean third-party testing (Layer 1) can still sell an ingredient with weak human evidence (Layer 2). A product with strong buyer sentiment (Layer 3) can still be covered only by affiliate reviews (Layer 4). The overall score weights the layers together, but the layers themselves never collapse into a single number on the way in.
The full weighting, the safety caps applied after weighting, and the rules for each layer are published. Read the scoring methodology →