Clarify SETA v2 model results in dataset stats

seta_v2/README.md

@@ -5,12 +5,12 @@
 - **v1 tasks:** 3,107
 - **Kept:** 2,246, solved at least once by either model, including historical recovery results.
 - **Excluded:** 861, no recorded success.
-- **Newly kept:** 2 since the previous release (2,244).
 - **Evaluated:** 3,107 tasks with 16 completed outcomes per model; 99,424 evaluation attempts.
 - **Pending evaluation attempts:** 0.
+- **Qwen/Qwen3-30B-A3B-Instruct-2507 (thinking off):** pass@16 **69.81%**, solving 2,169 of 3,107 tasks.
+- **Qwen/Qwen3-30B-A3B (thinking on):** pass@16 **47.67%**, solving 1,481 of 3,107 tasks.
 - **Combined trace records:** 112,008, including historical attempts.
 - **Saved conversations:** 111,700.
-- **v1 base revision:** `6ff346b330ed44d299b98474a96f591ff106bd8e`.
 
 ## Evaluation settings
 
@@ -127,17 +127,15 @@ Medians use recorded measurements only; sample counts and percentiles are in the
 Measured agent-environment peak memory has a median of **1,401.8 MB** across **6,024 Qwen/Qwen3-30B-A3B-Instruct-2507 attempts** and **1,356.9 MB** across **6,246 Qwen/Qwen3-30B-A3B (thinking) attempts**. [Resource distributions](metadata/runtime-resources.json) and [per-task peaks](metadata/per-task-memory.parquet) cover attempts with saved measurements only.
 
 - **Versions:** Apptainer **1.5.4**, Python **3.12.14**, Harbor **0.8.1**.
-- **Implementation:** [Marin Harbor `7faf878c14b6`](https://github.com/marin-community/harbor/tree/7faf878c14b6d72737579ec936ebf5f74ba3194d) + [our runtime patches](https://github.com/MLI-lab/OT-next-data/tree/main/harbor_patches).
+- **Implementation:** [Marin Harbor](https://github.com/marin-community/harbor/tree/7faf878c14b6d72737579ec936ebf5f74ba3194d) + [our runtime patches](https://github.com/MLI-lab/OT-next-data/tree/main/harbor_patches).
 
 Not yet checked with the repository-leak checks added on 2026-10-17 (leftover git history and file timestamps that could reveal the solution).
 
 ## Reproduce and select tasks
 
-`patch.py` rebuilds `tasks.parquet` from the pinned v1 revision and `metadata/selection.json`, verifying the source SHA-256.
+`patch.py` rebuilds `tasks.parquet` from the pinned v1 source recorded in [selection and provenance](metadata/selection.json), verifying the source SHA-256.
 
 ```python
 import pyarrow.parquet as pq
 subset = pq.read_table("tasks.parquet", filters=[("instruct_successes", "=", 1)])
 ```
-
-Results snapshot: **2026-10-20T19:16:08.279028+00:00**.