AutoScientist Part 2 source dataset

README.md

@@ -80,24 +80,24 @@ response states. Sharing a helper would let a wrong formula agree with itself.
 
 ## Adaption platform quality grade
 
-Graded by [Adaption](https://adaptionlabs.ai)'s own data-quality evaluation (dataset `a2a0c1ba-d061-45bd-9a97-80056fd26c0c`, sampled on 100 rows):
+Graded by [Adaption](https://adaptionlabs.ai)'s own data-quality evaluation (dataset `23942311-a24d-4930-b014-2d61eedcff73`, sampled on 100 rows):
 
 | | source (what we trained on) | after platform adaptation |
 |---|---|---|
-| Grade | **C** | **B** |
-| Score | 6.0 | 7.6 |
-| Percentile (all platform datasets) | 6.9 | **24.6** |
-| Prompt quality | 5.91 (pct 12.2) | 5.99 (pct 12.2) |
-| Completion quality | 4.02 (pct 1.6) | 9.17 (pct 37) |
+| Grade | **C** | **A** |
+| Score | 6.0 | 9.0 |
+| Percentile (all platform datasets) | 6.9 | **33** |
+| Prompt quality | 5.94 (pct 12.2) | 8.09 (pct 28.9) |
+| Completion quality | 4.66 (pct 1.6) | 9.87 (pct 37) |
 
-Improvement: **+26.7%**. All numbers, including the per-metric percentiles, are exactly as returned by the platform API (`eval/adaption_grade_*.json` in the build repo); where a before/after percentile repeats, that repetition is the platform's own coarse bucketing, not a transcription error.
+Improvement: **+50.0%**. All numbers, including the per-metric percentiles, are exactly as returned by the platform API (`eval/adaption_grade_*.json` in the build repo); where a before/after percentile repeats, that repetition is the platform's own coarse bucketing, not a transcription error.
 
 ## Concise vs expanded — the measurement that surprised us
 
 The platform's adaptation rewrites our 137-word answers into
 733-word ones and grades them far higher (completion quality
-4.02
-→ 9.17).
+4.66
+→ 9.87).
 Two experiments, both blinded and judged in both orderings:
 
 **1. Judging the reference text.** Our concise completions vs the platform's expanded