Combine visual and numeric checks
Blend appearance, size, defect tags, and yield indicators into one practical rank.
Use it as a comparison memo, not an resmi grade.
Return a reference rank even when numeric data is sparse.
Line up multiple lots with the same baseline.
Paylaşım by URL and keep a local copy in the tarayıcı.
Cocoon Grading Memo
Record the appearance, size, defects, and yield notlar for each lot, then compare them with the same yardstick.
Combine shell percent, filament length, and reelability to return a practical rank that is easy to paylaşım in the field.
Girdis are processed in this tarayıcı and never sent to a sunucu.
Surface severe defects early
Wet, mixed lot, mold, and hole conditions get separate and recheck markers.
Compare multiple lots side by side
Paste CSV data or import a file to get a ranked comparison table quickly.
Keep it local and paylaşım by URL
Leave data on the device, then copy a paylaşım URL only when you need to pass it on.
Notlar
This is a comparison memo, not an resmi grading result.
The target ranges for shell percent, filament length, and reelability vary by strain, region, and local practice.
Use wet, mixed lot, mold, and hole conditions as cues for separation or a recheck.
By default, the inputs are not sent to a sunucu.
Basics
Start with the lot identity and the state you want to compare.
- Enter the lot code and basic inspection details first.
- Record appearance, size, defects, shell percent, filament length, and reelability.
- Add more lots if you want to compare them in one table.
- Review the rank, score, and warnings, then paylaşım or export if needed.
Examples
Reference lot example
Girdi
Lot code: 2026-SP-03-A12 / appearance: good / size: uniform / shell percent: 20.5% / filament length: 1050m / reelability: 62% / defects: slight stain
Çıktı
Shown as an A rank with high confidence and only hafif warnings, suitable as a reference lot.
Sparse numeric data example
Girdi
Lot code: 2026-SP-03-B07 / appearance: fair / size: mostly uniform / defects: thin shell
Çıktı
Shown as a low-confidence memo driven mostly by appearance; extra numeric data improves the result.
Severe defect example
Girdi
Lot code: 2026-SP-03-C02 / appearance: poor / size: mixed / defects: wet, mixed lot
Çıktı
Flags for separate handling and recheck appear, and the warning stands out in the comparison table.
Glossary
Appearance rating
Stores the external look of the cocoon on an excellent / good / fair / poor scale.
Size rating
Records how uniform the cocoon size looks.
Defect tags
Fast labels for defect factors that reduce the rank or trigger a warning.
Shell percent
One of the main quality indicators for how much shell remains in the cocoon.
Filament length
How much silk thread can be drawn from the cocoon.
Reelability
How suitable the cocoon is for reeling.
Confidence
A kaba trust düzeyi based on the number of numeric indicators and sample count.
Batch comparison
Line up multiple lots and compare them with the same baseline.
Formulas
- Visual block = weighted average of appearance, size, and defect scores
- Quality block = weighted average of shell percent, filament length, and reelability
- Final score = weighted average of the two blocks - missing-metric penalty
- Rank = A / B / C / D using 80 / 65 / 50 thresholds
- Confidence = high / medium / low from the 3 numeric metrics and sample count
SSS
Can I use this as an resmi grade?
No. It is a memo for field comparisons, not an resmi grade certificate.
Does it work without numeric data?
Yes. It can still return a reference rank from appearance and defects, though confidence stays low.
What happens with severe defects?
Separate and recheck flags are added automatically.
Can I auto-sort multiple lots?
Yes. You can toggle rank-based sorting in ayarlar.
Where is the data stored?
By default, it stays in this tarayıcı. Export JSON or CSV if you want to move it elsewhere.
Can I switch units?
Yes. Weight supports g / oz, and filament length supports m / ft.