Evaluation-loss decrease over one logged interval

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Subtracting the current evaluation loss from the loss ten steps earlier gives a positive number when loss has fallen. It is an absolute change in loss units, not a percentage and not a derivative unless divided by elapsed time. Comparisons must use the same evaluation procedure at both checkpoints.

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4.2 Evaluation-loss increments

For observations ℓ10,ℓ20,…,ℓ300, define:

qt=ℓt−10−ℓt.

The largest qt identifies the ten-step interval with the greatest observed reduction. These values locate changes at ten-step resolution only. A decrease from step 160 to 170 cannot identify a unique event at any particular intervening update. Evaluation loss is not treated as behavioral alignment, declaration probability, awareness, or cognition.

4.3 A deliberately limited change-point fit

An exploratory two-line fit minimizes:

{q}_{t}={ℓ}_{t-10}-{ℓ}_{t}.

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