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Machine learning · Measurement
The training set moves the error 390x. Nothing predicts it.
Across 231 training-set choices the worst case moved by a factor of 390. I tested nine cheap ways to pick a good one. None of them held up.
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Machine learning · Measurement
The metric was measuring my model, not the problem
A transferability score held at 0.54 across two independent budgets, then collapsed to 0.14 when I changed the model class. It was tracking the algorithm.
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Supply chain · Measurement
You cannot count the sale you did not make
Sales data records what you sold, not what people wanted. The two differ exactly on the days they matter most, and the gap teaches a forecast to shrink.
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Coding theory · Supply chain
A scratched label still scans, and that is not luck
A check digit tells you a barcode scan was wrong. Reed–Solomon parity tells you what it should have been. That difference decides what a damaged label costs.
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Vision science · Display engineering
Why a screen cannot measure vernier acuity, and how close it gets
A screen pixel at 60 cm subtends about 90 arcseconds; clinical vernier thresholds are 2–5. Antialiasing still measures below one pixel. Here is the arithmetic.
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Machine learning · Supply chain
My model scored perfect and that was the problem
A perfect held-out score measured one thing: whether the model could repeat what it had seen. Of 30 cross-family tests, 20 fell below a crude baseline.