How GradeThread grades
A condition grade is only trustworthy if the method behind it is open to inspection. This page documents how the GradeThread model is trained and evaluated, exactly what a grade does and doesn't claim, how we handle errors, and where human judgment sits in the loop — the same standard we'd want from anyone grading our own items.
How the model is trained
Every garment is scored against one fixed rubric — five weighted factors (Fabric Condition 30%, Structural Integrity 25%, Cosmetic Appearance 20%, Functional Elements 15%, Odor & Cleanliness 10%) combined into a single 1.0–10.0 grade. The model learns from graded examples with expert human reviewers correcting its output, and those corrections — plus real post-sale outcomes — feed a continuous accuracy loop. See the full rubric on the grading standard.
What a grade claims — and doesn't
A grade is
- An objective assessment of physical condition
- Reproducible against a published rubric
- Independently verifiable via a certificate
A grade is not
- An authentication — condition vs. authenticity
- An appraisal of monetary value
- A guarantee of fit or sizing
Error handling & human review
Every grade carries a confidence score. When confidence falls below our threshold, the submission is routed to a human reviewer before the grade is finalized — low-confidence cases never ship unchecked. Buyers can dispute a grade, reviewer corrections feed back into the accuracy loop, and every new model version must clear a fixed eval gate against a golden set of expert-graded garments before it grades live items. We publish the resulting platform-wide accuracy on the transparency report.
Methodology FAQ
- How is GradeThread's grading model trained?
- The model learns from a corpus of pre-owned garments graded against one fixed rubric — five weighted factors (fabric, structure, cosmetics, function, odor) combined into a 1.0–10.0 score — with expert human reviewers correcting the AI's grades. Those corrections, plus post-sale outcomes, feed a continuous accuracy loop, and every new model version must clear a fixed eval gate against a golden set of expert-graded items before it can grade live.
- What does a GradeThread grade claim — and not claim?
- A grade is an assessment of a garment's physical CONDITION against a published rubric: wear, damage, structural soundness, function, and cleanliness. It is not an authentication (it doesn't verify a brand or that an item is genuine — see grading vs. authentication), not an appraisal of monetary value, and not a guarantee of fit. It grades condition, objectively and reproducibly, and nothing more.
- How does GradeThread handle grading errors?
- Every grade carries a confidence score. When confidence falls below threshold, the submission is routed to human review before the grade is finalized, so low-confidence cases never ship unchecked. Buyers can dispute a grade, reviewer corrections feed back into the accuracy loop, and platform-wide agreement and error rates are published on the transparency report.
- Are humans involved in grading?
- Yes. Human reviewers correct low-confidence grades before they finalize, adjudicate disputes, and maintain the golden set that gates every model release. The AI does the volume; humans hold the standard.
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