results: select four-probe least-squares SDIL

1 files changed, 20 insertions, 0 deletions

diff --git a/RAIN_EP_RELEASED_PROFILE.md b/RAIN_EP_RELEASED_PROFILE.md
index 1d52ad6..adb6749 100644
--- a/RAIN_EP_RELEASED_PROFILE.md
+++ b/RAIN_EP_RELEASED_PROFILE.md
@@ -183,3 +183,23 @@ four budgets lose to retaining the last measured intercept. This closes
 cadence/probe-budget tuning for the current predictor; further work must change
 the local identification rule and then re-enter through a new development
 screen rather than scaling this implementation.
+
+## R6 local least-squares development screen
+
+R6 changed only the affine predictor's local identification rule from
+normalized LMS to online least squares. Each parameter stores its own running
+state/measurement statistics; it receives no label, clean update, generated
+bias coefficient, or nonlocal value. The matched upfront-probe experiment was
+then repeated on the same seed and split:
+
+| upfront probes | intercept tracker | least-squares SDIL | SDIL minus intercept |
+|---:|---:|---:|---:|
+| 2 | 43.75% | 44.65% | +0.90 points |
+| 4 | 41.30% | 45.35% | +4.05 points |
+| 8 | 44.90% | 46.10% | +1.20 points |
+| 16 | 45.45% | 45.90% | +0.45 points |
+
+Least-squares SDIL wins all four equal-budget comparisons. At four probes it
+recovers 45.35% versus 41.30% for the tracker and a 46.00% clean/oracle
+reference from R1. This is positive development evidence, not confirmation;
+the four-probe point is frozen for the next paired-seed check.