diff --git a/swelego_v2/README.md b/swelego_v2/README.md
index dbe848e47dcb8b183b766953d0c6b73578820347..0516fbc8bff0e716ff2435126241836503cd57ca 100644
--- a/swelego_v2/README.md
+++ b/swelego_v2/README.md
@@ -8,14 +8,14 @@
 - **Newly kept in this update:** 5
 - **Tasks with recorded attempts:** 4,277 / 4,277
 - **Recorded attempts:** 34,216
-- **Available conversations:** 18,678
-- **Missing conversations:** 15,538
-- **Unknown attempt outcomes:** 1,331 across 450 tasks
-- **Tasks with all eight classified outcomes:** 3,827 / 4,277
+- **Available conversations:** 32,803
+- **Missing conversations:** 1,413
+- **Unknown attempt outcomes:** 0
+- **Tasks with all eight classified outcomes:** 4,277 / 4,277
 - **Task payload changes:** 0
 - **v1 base revision:** `819fe8c3809d9a393502017055c21057b21f02fd`
 
-Results snapshot: **2026-10-20T19:39:53.280360+00:00**. This release selects tasks with at least one observed teacher success and preserves the pinned v1 task payloads.
+Results snapshot: **2026-10-21T22:05:46.361970+00:00**. This release selects tasks with at least one observed teacher success and preserves the pinned v1 task payloads.
 
 ## Evaluation settings
 
@@ -35,13 +35,13 @@ The table reports settings found in **6 sampled saved trial configurations**, no
 
 | Model | Tasks attempted | Recorded attempts | Tasks with all 8 classified outcomes | Tasks solved |
 | --- | ---: | ---: | ---: | ---: |
-| Qwen3-30B Instruct | 4,277 / 4,277 | 34,216 | 3,827 / 4,277 | 1,245 |
+| Qwen3-30B Instruct | 4,277 / 4,277 | 34,216 | 4,277 / 4,277 | 1,245 |
 
 The teacher is `Qwen/Qwen3-30B-A3B-Instruct-2507`, using Terminus-2 and eight attempts per task. The completed 12-task Helma rerun is now included: **96 attempts with saved trajectories and five newly solved tasks**. One rerun attempt ended with `TmuxSessionEndedError`; its raw verifier grade remains missing and its outcome reward is zero under the terminal-error policy. [Rerun selection](metadata/rerun-selection-20261020.json) and [stage-6/7 reports and contract](metadata/rerun-reports-20261020.tar.gz) preserve the evidence.
 
 The rerun preserves temperature 0.7, top-p 0.8, top-k 20, a 32,768-token context and an intended 8,192-token response limit (see evaluation settings). Stage-6 and stage-7 reports are complete for all 12 rerun tasks. These teacher stages do not establish a new full datasource-validation result.
 
-Dataset-wide pass@k estimates remain unavailable because 1,331 historical outcomes are unknown. They are not counted as failures.
+Over all 4,277 tasks and 34,216 attempts, pass@1 is **10.73%**, pass@4 **22.25%** and pass@8 **29.11%** (unbiased estimates). Recorded terminal errors count as unsolved, including 1,412 attempts whose environment or setup failed before the agent started, so these rates are lower bounds for the model.
 
 ### Successful attempts among kept tasks
 
@@ -56,21 +56,26 @@ Dataset-wide pass@k estimates remain unavailable because 1,331 historical outcom
 | 7/8 | 58 |
 | 8/8 | 72 |
 
-Counts reflect recorded successes; unknown historical outcomes remain unknown.
+Counts reflect recorded successes. The recovery below changed no success count.
 
 ## Evidence and trajectories
 
-The combined `traces/` files contain **34,216 unique attempt records**, including kept and unselected tasks. **18,678** have saved conversations. Original result JSON is preserved where available, together with raw verifier rewards, outcome rewards, task-version hashes and the current selection flag.
+The combined `traces/` files contain **34,216 unique attempt records**, including kept and unselected tasks. **32,803** have saved conversations. Original result JSON is preserved where available, together with raw verifier rewards, outcome rewards, task-version hashes and the current selection flag.
 
-### Missing historical evidence in the HF files
+### Recovered historical evidence
 
-- **15,538 attempt rows lack a saved conversation.** Their attempt records are present. A missing conversation does not by itself mean that the verifier outcome is unknown.
-- **1,580 attempts lack a raw verifier grade.** Of these, **249** have classified terminal-error outcomes and count as reward zero. The other **1,331** have unknown outcomes and no original result JSON in the trace rows; they remain unknown.
-- **450 tasks lack eight classified outcomes** because of these historical unknowns. All 4,277 tasks now have eight attempt records; the 12-task rerun is no longer pending.
+On 2026-10-22, the missing fields were filled from the original stage-6 evidence archives of the RWTH (CLAIX) run `swelego-recovery-20261015-c25g` (206 archives). Fields were filled only where the published rows were empty; no published value changed.
 
-These gaps overlap and should not be added together. Recovery from original run archives remains pending; empty fields do not establish that the original traces were lost.
+- **Result JSON:** 15,360 attempts gained their original result record.
+- **Conversations:** 14,125 attempts gained their saved trajectory.
+- **Unknown outcomes:** all 1,331 are recorded terminal errors without a verifier grade, so they now score zero under the terminal-error policy. 1,235 of them failed before the agent started (mostly a task-executor start failure and task-setup exits on RWTH). No task gained a success, so the kept set is unchanged.
 
-[Trace statistics](trace_stats/README.md) and plots have been regenerated from this published snapshot, including the 96 rerun attempts. Missing measurements are kept separate from measured outcomes.
+### Remaining gaps
+
+- **1,413 attempts have no saved conversation.** 1,412 never produced one because the attempt ended before or during agent start; one attempt (`fsspec__filesystem_spec-1273`) has a verifier grade but no source archive.
+- **1,580 attempts have no raw verifier grade.** All are recorded terminal errors and count as reward zero.
+
+[Trace statistics](trace_stats/README.md) and plots have been regenerated from this snapshot, including the recovered conversations and the 96 rerun attempts. Missing measurements are kept separate from measured outcomes.
 
 ## Reproduce and select tasks
 
diff --git a/swelego_v2/metadata/selection.json b/swelego_v2/metadata/selection.json
index 1a993ec4a56f94de9329f9fddd9a1a870cbf42bb..f596c1e6c0ef8379fa490daaea045225752823ec 100644
--- a/swelego_v2/metadata/selection.json
+++ b/swelego_v2/metadata/selection.json
@@ -1 +1 @@
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terminal errors score zero; raw verifier rewards are preserved. Historical unknown outcomes remain unknown.","trace_policy":"All previous selected attempt IDs plus the 96 attempts from the completed 12-task rerun. No failed submissions or duplicate race copies are added."},"result_columns":["instruct_successes","instruct_graded_attempts","instruct_missing_attempts","target_attempts_per_model","instruct_verifier_graded_attempts"],"reward_policy":"terminal-errors-zero-v2","trace_recovery":{"baseline_revision":"642a47baeec7edc3b0db072554c7170ca0ea87dd","snapshot_utc":"2026-10-21T22:05:46.361970+00:00","source":"RWTH CLAIX runs/swelego-recovery-20261015-c25g, 206 stage-6 evidence archives","filled":{"result":15360,"trajectory":14125,"reward":1331,"reward_origin":1331,"selection_reward":1331},"changed_trace_files":198,"policy":"Fields are filled only where empty; recorded terminal errors score zero (terminal-errors-zero-v2)."}}
\ No newline at end of file
diff --git a/swelego_v2/tasks.parquet b/swelego_v2/tasks.parquet
index 39ca0b933e0f51fcd0828a8e54601c8704e8b8c2..4987896b96a10d562c9f94e47d0906b21912047d 100644
--- a/swelego_v2/tasks.parquet
+++ b/swelego_v2/tasks.parquet
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:095268bf849c864428e9fa3922f6243051cbb7e490e8a369a3d8b5394f51364a
-size 5621360
+oid sha256:12ab2bdfb99684a5ed6d34169b77c7cf6264fb7489b37fa408aa217732b47706
+size 5622127
diff --git a/swelego_v2/trace_stats/README.md b/swelego_v2/trace_stats/README.md
index 9a3c109cd1b9af5c061cb02e10c1e8c15848e61f..4ebc7850e0e1e3062e6da3601ae26aef972ed107 100644
--- a/swelego_v2/trace_stats/README.md
+++ b/swelego_v2/trace_stats/README.md
@@ -6,10 +6,10 @@
 | --- | ---: |
 | Recorded attempts | 34,216 |
 | Median agent turns | 15 |
-| Median input tokens per attempt | 96,423 |
-| Median output tokens per attempt | 4,814 |
-| Median agent runtime (seconds) | 101 |
-| Median verifier runtime (seconds) | 9 |
+| Median input tokens per attempt | 98,424 |
+| Median output tokens per attempt | 4,885 |
+| Median agent runtime (seconds) | 100 |
+| Median verifier runtime (seconds) | 7 |
 
 Medians use recorded measurements only.
 
@@ -31,7 +31,10 @@ Per-model plots: [instruct](plots/instruct-trace-commands.png), [instruct](plots
 - [Per-task metrics](data/per_task.parquet) and [per-attempt metrics](data/per_attempt.parquet), with nested metrics stored as JSON.
 - [Provenance](data/provenance.json): source files and deduplication.
 
-Attempts without a saved conversation: 15,538; without a verifier reward: 1,580. Their missing measurements stay empty.
+Attempts without a saved conversation: 1,413; without a verifier reward: 1,580. Their missing measurements stay empty.
+
+
+Evaluation budgets: see the [dataset evaluation setup](../README.md). Per-call context and output-limit enforcement are not established by token-usage statistics.
 
 ## Evaluation settings
 
diff --git a/swelego_v2/trace_stats/data/per_attempt.parquet b/swelego_v2/trace_stats/data/per_attempt.parquet
index bbe0a364d9cc5d32083d102fb2edc27f9dd9878d..30801c6c85f143a80b7d5cc9744cfbdcde4c4f8e 100644
--- a/swelego_v2/trace_stats/data/per_attempt.parquet
+++ b/swelego_v2/trace_stats/data/per_attempt.parquet
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4811265ee47cf5dd1f4ef74fd1eec482452d4d8d9b1fa5b7e95799744c073103
-size 3982459
+oid sha256:7cfeed9f33754479ec396878f2f988447a39374015a077b6a52eb31f4556d4ce
+size 5701228
diff --git a/swelego_v2/trace_stats/data/per_task.parquet b/swelego_v2/trace_stats/data/per_task.parquet
index 3fa9ed88a08b5d92880ac5d37f645524ea18faec..c8c2bf69bb815e6a886ad430e9ef0d14ec3678a8 100644
--- a/swelego_v2/trace_stats/data/per_task.parquet
+++ b/swelego_v2/trace_stats/data/per_task.parquet
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:16296906f68af06b4b4a2802e051321dd4abfbb8fddbd4c8b0b3dcc888fd9fcd
-size 1368772
+oid sha256:19ec1e760c784015c428033ff466595d33667ff9f4a62a171992eaa0df2d325c
+size 2394626
diff --git a/swelego_v2/trace_stats/data/provenance.json b/swelego_v2/trace_stats/data/provenance.json
index b481dc3664a2942cbf3b94d661366ac869f683cb..054c944421f3bdcbd98223f96aaa20369f73194f 100644
--- a/swelego_v2/trace_stats/data/provenance.json
+++ b/swelego_v2/trace_stats/data/provenance.json
@@ -16,7 +16,7 @@
    "file": "traces/part-0001.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "db8a5a796574f968a5db4b72ffeafdd48e72b0dfb3daac98bbfe93ba235e7d1c"
+   "sha256": "7fbe732fd953489418c99938412b5a520c6656cbdfda2dc94641c3ccde8ab931"
   },
   {
    "file": "traces/part-0002.parquet",
@@ -34,13 +34,13 @@
    "file": "traces/part-0004.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "df368c592ecb0929ccb3bf6c2f3597b9c0d3cc40db8b58fc7af6faf33f4d4716"
+   "sha256": "272e4095ac9727dbcf6daea3307f81a97c88f2d550195f3a6bbffb8ce9d90f81"
   },
   {
    "file": "traces/part-0005.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "e3276cd664d53227dc389e6d14d3a37283ffe93a3fd6c3f03653699f5a3dd65b"
+   "sha256": "7a0ceb88a8734abf07f33e788436b2bbefb7b971716a284c6f8cf9d154673ba3"
   },
   {
    "file": "traces/part-0006.parquet",
@@ -58,91 +58,91 @@
    "file": "traces/part-0008.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "3c2f62a63811ef1fe0d8c48ea192251b549684c30b2fda9ee76f735acb6aeffb"
+   "sha256": "126c0389d57972cddd77b440baae3af5961985e49dabe53cba7d39a6dd19b1ee"
   },
   {
    "file": "traces/part-0009.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "e174b411ba1e27756aebc5fc270fd81585c4ce70a36fd5d5f81cc133de8317f6"
+   "sha256": "afad136e71f39ce10870190df770e171f0d64894eece91a8c42b2a7222c74353"
   },
   {
    "file": "traces/part-0010.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "e7fbf1a182d43b9542e3e067becb36ff426085183895660ae8ee63205b126775"
+   "sha256": "5801ac10aabac0b688f599e9015077b7b24e3c84e15fd2b1a546b7080703f3d9"
   },
   {
    "file": "traces/part-0011.parquet",
    "rows": 128,
    "unique_rows_added": 128,
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+   "sha256": "4cef2e03c8ae489ef7f1fbc514c13f049d8e247285b61d5963be370e2ef11a21"
   },
   {
    "file": "traces/part-0236.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "a7a4ea74652ebf53941a9f50034ad1dcfd51c3cf73db3dd2f9a855d0b0ee8de3"
+   "sha256": "c47c0fe2ee67caaf5821b3d997bfd13825b0478f6eddd2f0d28307ac1f23375a"
   },
   {
    "file": "traces/part-0237.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "37c92ffb2ed45ac1f5d6cab382bcb9c733856290402859f1f163edf054a889bc"
+   "sha256": "a68602dea08b8318d73b76d135a0b01ad94655fc57a61e5770802047d11a5562"
   },
   {
    "file": "traces/part-0238.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "a11918f22d27ae815d62ef4b8dd241b2f7bf5948425089e2df4c3feae65b16e4"
+   "sha256": "4390fa549aabeb31ca7055a15e36f92c80e539713e650119a8c0faf81362b5c0"
   },
   {
    "file": "traces/part-0239.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "9e7609e412412bf350d130d731c8a5960ec5c56df499bd536551581793d9df5b"
+   "sha256": "1ece5165e2f33c478ba75787c5f750f1663df77c5289840853b9120e5e0e1f66"
   },
   {
    "file": "traces/part-0240.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "7a3415e29411dee1b9fca78ac11b9327631bd6706617357381ccf2fefee7ece8"
+   "sha256": "bdb91d803c879f3fc97aacc6ea734eb34e2e80edc987d6175ecac9c496080bb9"
   },
   {
    "file": "traces/part-0241.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "7324fd991351d07273bdbf1b912805da92a57bc78602a3b654f17e75301e5751"
+   "sha256": "691410bc03b5f47cb9d32641a0e75d8e8b4f50b80320ff950d14611dd929f07d"
   },
   {
    "file": "traces/part-0242.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "d0a024d80fd0d881834488fb92dcfe3819d3e956ee8c14cb471859e7c118cf02"
+   "sha256": "afbdc407522edb2797361306f3ec39f24d8cd8276392f8b102e803aae3def5b5"
   },
   {
    "file": "traces/part-0243.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "7cb1c181bef88dd30352abb81786d25ef28785ed118deadd7d97bee8097100d8"
+   "sha256": "5af65f6eb191f55f73d178dc2d6d430a20cad61cd5ad766c655c0ca6ed7c8399"
   },
   {
    "file": "traces/part-0244.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "31d30a7277643b76aad8ea5662d5a5dc0361a1339bf1606bcd47915fcecd5cc5"
+   "sha256": "2f681a7e3cda9a6c1cc679c55d1ff5997b84875fe55e3e01af1e942866b2a75a"
   },
   {
    "file": "traces/part-0245.parquet",
@@ -1486,13 +1486,13 @@
    "file": "traces/part-0246.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "9ff81ec607d1205d44511b8d09104c865d88d91213620aa269402605fec7332f"
+   "sha256": "5f62ccbd15e028f8feba145f2b9d8bf15f7914dd9b21dc17b325dff97cce7cda"
   },
   {
    "file": "traces/part-0247.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "9945089550599c9302ac3d3ff6fcb620d1469c2385299c9e4ede25a2befd2388"
+   "sha256": "e833241d3e134643b09cd09acf7f86095f6dde882ca1e8532ce40fb686495127"
   },
   {
    "file": "traces/part-0248.parquet",
@@ -1504,7 +1504,7 @@
    "file": "traces/part-0249.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "561cbd0fb63d223d50eeb635541e3768729f5e16f7b41f92f7aced8a4641c899"
+   "sha256": "23ebacc1970b458000a96750285cec4cec74a315d9625857bb6b1de4fd962330"
   },
   {
    "file": "traces/part-0250.parquet",
@@ -1528,85 +1528,85 @@
    "file": "traces/part-0253.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "4e36642acd5c3ab37e2e9897ad684cea00470cff12af2583fb17716cb720a1cf"
+   "sha256": "fa716be0ca9f9cb841ccc1dabf532cb2b6b9e60b24df58b98b17fbd1d24d2278"
   },
   {
    "file": "traces/part-0254.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "8b82c2641419bd8b0298c3be2bbed67f644ea46478d07dfb7accbfa3f4643a3f"
+   "sha256": "8da50642f76f3ae63ac51815c471feaf66bae7f614a249ac92f8ac619b0629a1"
   },
   {
    "file": "traces/part-0255.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "6bfd2db659ca2e53aa751e3004c338d35a858566326e11fa650d2b435d916a11"
+   "sha256": "7dbcd03087475495421efe68aaa88ea3f8bb0b2f74cb118ba2e9c1a369761d19"
   },
   {
    "file": "traces/part-0256.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "c841bcfe24ba1451cb40e08388f83af7716653a61c4ca39bad58f0aafa660038"
+   "sha256": "8bf947b80b2cf0bbd123591b7836c103260f968a0aaf7b439572b763859fa6ec"
   },
   {
    "file": "traces/part-0257.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "3a5acdeb91338144a78c6dfff53589e8773810eef55f12148790eb34a6f3577a"
+   "sha256": "5b39fca2f63729e9c48e1cc430829e4324ce0e152b5f2540b4929a8434b0f6ae"
   },
   {
    "file": "traces/part-0258.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "f8a466df9aac59b437cdb34a00ff35935b18a9325888285d709f950cabc5aff3"
+   "sha256": "ddb0afb03cc3fcabf3587fefe482afddd3099bf0fc70af2d6245df37dc445514"
   },
   {
    "file": "traces/part-0259.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "6f73a9351c840b8c91e5b5ed56c35c4b0fbd3bef778aafb8b34225ef9fbd486c"
+   "sha256": "aacfec34889ca606cae350cc5a39193fc09baedbd0fe8692025a350463b47242"
   },
   {
    "file": "traces/part-0260.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "1c2e82d10c2e0f4e8e2cf786caea0efac572db4f9713666fd1576a9fd839d879"
+   "sha256": "044e30cd97279dd119c1c192034983b844c411cba3fab04a23e5fc2f990d6c4e"
   },
   {
    "file": "traces/part-0261.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "76ab60b38d6447b536fe002b328c7201904835bcae76a44590c4cc5c22d625d6"
+   "sha256": "76b9a41afaa1ad91dc85668a6da39787e3ba14c04e61befae36b9e90422f687f"
   },
   {
    "file": "traces/part-0262.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "41d75d991bfd333a1c0ff5b41fbc72a313a0493adc39412039bff4cedf98aac9"
+   "sha256": "77da8010f1aa55326ced5a3099ab2d596bc2c84701bee1f63795d521bd74da43"
   },
   {
    "file": "traces/part-0263.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "caa1b8992babea0d72a85fafbb20024a89665d9f59b1411bda433a54b15c3eb3"
+   "sha256": "ad372036be9d852031d5f09f2d608d1694804b3acd1aa7a520816411a4ad02b9"
   },
   {
    "file": "traces/part-0264.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "488e280c51e0c2da9eecef468155264a6670316b074a859e7072e323d7cfa716"
+   "sha256": "ef6fa20f21e9fc7721e7cbdc443a393326f66e6f8049b84d0428e17495f999d2"
   },
   {
    "file": "traces/part-0265.parquet",
    "rows": 128,
    "unique_rows_added": 128,
-   "sha256": "9df02a80be44cc64d0a8ba1e83c4d501c304157905e9ab15ca2be19ea4152d7d"
+   "sha256": "eecdb96f295e6f75b29032a3fe4c0f26ed857b0fc8f21ca2cac99bdf29b67551"
   },
   {
    "file": "traces/part-0266.parquet",
    "rows": 72,
    "unique_rows_added": 72,
-   "sha256": "dcfbd54a353f70966448b9cac5f4f110f9820d6d77e918e0ecfb3ba6c6678e16"
+   "sha256": "0617e47476fd1cefbf22f2d890e3a184d8e1c4b96a355bd5e682d23921e38461"
   },
   {
    "file": "traces/part-0267.parquet",
diff --git a/swelego_v2/trace_stats/data/summary.json b/swelego_v2/trace_stats/data/summary.json
index 3bed7e0b0e39df25e187edf611ccdee09af284f7..2c14e351fbc0f109868e556a65ff88fb6b7de8a6 100644
--- a/swelego_v2/trace_stats/data/summary.json
+++ b/swelego_v2/trace_stats/data/summary.json
@@ -1,2094 +1,3363 @@
 {
  "scope": "All attempts in the published trace Parquets of this folder.",
- "created_at": "2026-10-20T19:46:50.550218+00:00",
+ "created_at": "2026-10-21T22:07:12.504617+00:00",
  "input_rows": 34216,
  "duplicate_records_removed": 0,
  "unique_attempts": 34216,
  "unique_tasks": 4277,
- "missing_trajectories": 15538,
+ "missing_trajectories": 1413,
  "null_verifier_rewards": 1580,
  "all_attempts": {
   "trajectories": 34216,
-  "graded": 32885,
+  "graded": 34216,
   "solved": 3673,
   "turns": {
-   "n": 18679,
-   "mean": 35.56068312008137,
+   "n": 32804,
+   "mean": 36.34032435068894,
    "median": 15,
-   "p90": 100,
-   "p95": 131,
+   "p90": 102,
+   "p95": 133,
    "max": 532
   },
   "input_tokens": {
-   "n": 18679,
-   "mean": 473764.73317629425,
-   "median": 96423,
-   "p90": 1600363,
-   "p95": 2102694,
+   "n": 32804,
+   "mean": 486974.6387635654,
+   "median": 98424,
+   "p90": 1649575,
+   "p95": 2149043,
    "max": 7547249
   },
-  "input_tokens_total": 8849451451,
+  "input_tokens_total": 15974716050,
   "output_tokens": {
-   "n": 18679,
-   "mean": 20227.20477541624,
-   "median": 4814,
-   "p90": 72841,
-   "p95": 92112,
+   "n": 32804,
+   "mean": 20926.337885623703,
+   "median": 4885,
+   "p90": 75449,
+   "p95": 95105,
    "max": 177685
   },
-  "output_tokens_total": 377823958,
+  "output_tokens_total": 686467588,
   "peak_context_tokens": {
-   "n": 18678,
-   "mean": 15533.973498233216,
-   "median": 12240,
-   "p90": 25525,
-   "p95": 37500,
+   "n": 32803,
+   "mean": 15647.885742157729,
+   "median": 12380,
+   "p90": 25606,
+   "p95": 37553,
    "max": 75990
   },
   "peak_context_fraction": {
-   "n": 18678,
-   "mean": 0.4740592498240117,
-   "median": 0.37353515625,
-   "p90": 0.778961181640625,
-   "p95": 1.1444091796875,
+   "n": 32803,
+   "mean": 0.4775355756273721,
+   "median": 0.3778076171875,
+   "p90": 0.78143310546875,
+   "p95": 1.146026611328125,
    "max": 2.31903076171875
   },
-  "trajectories_above_90_percent_context": 1470,
+  "trajectories_above_90_percent_context": 2638,
   "latency_seconds": {
    "model_call": {
-    "n": 722730,
-    "mean": 3.673963768780788,
-    "median": 2.972688674926758,
-    "p90": 6.280731439590454,
-    "p95": 8.250241994857788,
+    "n": 1299366,
+    "mean": 3.6925861979094265,
+    "median": 2.996037721633911,
+    "p90": 6.303562641143799,
+    "p95": 8.32641077041626,
     "max": 194.6667640209198
    },
    "tool_call": null,
    "agent": {
-    "n": 18679,
-    "mean": 310.4635393002302,
-    "median": 101.364684,
-    "p90": 1200.001296,
-    "p95": 1200.002014,
+    "n": 32804,
+    "mean": 313.7772989879283,
+    "median": 99.843167,
+    "p90": 1200.001323,
+    "p95": 1200.002003,
     "max": 1200.424272
    },
    "verifier": {
-    "n": 18649,
-    "mean": 14.536699102740094,
-    "median": 9.371719,
-    "p90": 17.051955,
-    "p95": 26.99541,
+    "n": 32733,
+    "mean": 12.479692699019338,
+    "median": 7.462351,
+    "p90": 14.514424,
+    "p95": 21.239582,
     "max": 1810.003261
    },
    "trial": {
-    "n": 18856,
-    "mean": 401.7832565874523,
-    "median": 182.096659,
-    "p90": 1237.318994,
-    "p95": 1261.868722,
+    "n": 34216,
+    "mean": 386.0666456013561,
+    "median": 165.755846,
+    "p90": 1232.192095,
+    "p95": 1256.14995,
     "max": 4731.866045
    }
   },
   "tools": {
    "bash_command": {
-    "calls": 1270602,
-    "calls_per_trajectory": 37.13473228898761,
+    "calls": 2303283,
+    "calls_per_trajectory": 67.31596329202712,
     "failed": null,
     "failure_rate": null
    },
    "mark_task_complete": {
-    "calls": 33572,
-    "calls_per_trajectory": 0.9811783960720131,
+    "calls": 58769,
+    "calls_per_trajectory": 1.7175882628010288,
     "failed": null,
     "failure_rate": null
    }
   },
-  "tool_steps": 549566,
+  "tool_steps": 987859,
   "tool_steps_without_output": 0,
-  "tool_steps_with_error_text": 226210,
-  "tool_steps_with_error_text_rate": 0.41161571130674024,
+  "tool_steps_with_error_text": 404555,
+  "tool_steps_with_error_text_rate": 0.4095270681342175,
   "terminations": {
-   "environment_error": 3,
-   "not_recorded": 14029,
-   "other_error": 213,
-   "session_ended": 49,
-   "task_complete": 16327,
-   "task_memory_limit": 10,
-   "task_timeout": 2244,
-   "verifier_error": 1341
+   "environment_error": 38,
+   "other_error": 1462,
+   "session_ended": 83,
+   "task_complete": 28520,
+   "task_memory_limit": 24,
+   "task_timeout": 4060,
+   "verifier_error": 29
   },
   "command_distribution": {
-   "\n": 1.989841018001075e-05,
-   "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with ZipFile(fname, 'r') as zf:\n            zf.extractall(path=extract_dir, members=self.members)\n\n\nclass Untar(ExtractorProcessor):\n    ": 4.780260964006547e-07,
-   "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with tarfile.open(fname, 'r') as tf:\n            tf.extractall(path=extract_dir, members=self.members)\n\nclass Decompress(ExtractorProcessor):\n    ": 4.780260964006547e-07,
-   "\n\n    def __init__(self, method=auto, name=None):\n        self.method = method\n        self.name = name\n\n    def __call__(self, fname, action, pooch):\n        if self.name is None:\n            decompressed = fname + .decomp\n        else:\n            decompressed = os.path.join(os.path.dirname(fname), self.name)\n        if action in ('update', 'download') or not os.path.exists(decompressed):\n            get_logger().info(\n                Decompressing": 4.780260964006547e-07,
-   "\n        error_archives = To": 4.780260964006547e-07,
-   "\n        if not len(ground_truth_answers) == len(predicted_answers):\n            raise ValueError(The": 8.111957999526262e-07,
-   "\n        raise NotImplementedError\n\n\nclass Unzip(ExtractorProcessor):\n    ": 4.780260964006547e-07,
-   "\n        return self.converter.map_to_openapi_type(field_type)(cls)\n": 2.230788449869722e-06,
-   "\n        return self.map_to_openapi_type(field_type)'); else: print(line, end='')": 1.9398160433649757e-07,
-   "\n    # Get parents of the node\n    parents = set(model.get_parents(node))\n\n    # Get children of the node\n    children = set(model.get_children(node))\n\n    # Get other parents of children (i.e., parents of children excluding the node itself)\n    other_parents = set()\n    for child in children:\n        child_parents = set(model.get_parents(child))\n        other_parents.update(child_parents - {node})\n\n    # The Markov blanket is the union of parents, children, and other parents of children\n    markov_blanket = parents | children | other_parents\n\n    return markov_blanket": 2.230788449869722e-06,
-   "\n    client = _compute_client_factory()\n    return _get_vmss_instance_view(client, resource_group_name, vm_scale_set_name, instance_id)": 5.147973345853205e-07,
-   "\n    from .core import Array\n    from .utils import meta_from_array\n    import numpy as np\n    \n    if meta is None:\n        meta = np.empty(shape, dtype=dtype)\n    \n    if chunks is None:\n        chunks = shape\n    \n    return Array(\n        name=name,\n        shape=shape,\n        dtype=dtype,\n        chunks=chunks,\n        meta=meta,\n    )": 2.878436709509319e-07,
-   "\n    http_code = httpstatus.CONFLICT\n": 3.824208771205237e-06,
-   "\n    plugin = MarshmallowPlugin()\n    return plugin.map_to_openapi_type(field_type)\n": 9.39279347313567e-07,
-   "\n    return e\n": 1.427704607916622e-07,
-   "\n    return self.converter.map_to_openapi_type(field_type)\n": 2.059189338341282e-06,
-   "\npython": 6.654555375882561e-06,
-   "                elif char == ": 1.4353598605059873e-07,
-   "        result.setdefault('typedefs', 0)": 1.394242781168576e-07,
-   "        return self.__dict__": 1.5563640347928294e-07,
-   "        self.__dict__.update(state)": 1.5563640347928294e-07,
-   "    def __getstate__(self):": 1.5563640347928294e-07,
-   "    def __setstate__(self, state):": 1.5563640347928294e-07,
-   "    def resolve_type(self, string, result):  # recursive": 1.394242781168576e-07,
-   "    try:\\n        filename = to_native_str(content_disposition, encoding=encoding).split(\\\\": 2.2685984235963274e-07,
-   " + ": 4.5166790275150584e-06,
-   " + n\n            overline += ": 9.66406548680024e-08,
-   " + n\n        elif (not el.previous_sibling\n              and (el.parent.name == table\n                   or (el.parent.name == tbody\n                       and not el.parent.previous_sibling))):\n            # first row, not headline, and:\n            # - the parent is table or\n            # - the parent is tbody at the beginning of a table.\n            # print empty headline above this row\n            overline += ": 9.66406548680024e-08,
-   " + n\n        return overline + ": 9.66406548680024e-08,
-   " + n\n')\n            break\n\n# Write back\nwith open('__init__.py', 'w') as f: f.writelines(lines)": 1.4089190209703507e-06,
-   " + n\n')\n            lines.insert(i + 15, '        overline += ": 1.4089190209703507e-06,
-   " + n\n')\n            lines.insert(i + 6, '    elif (not el.previous_sibling\n')\n            lines.insert(i + 7, '          and (el.parent.name == table\n')\n            lines.insert(i + 8, '               or (el.parent.name == tbody\n')\n            lines.insert(i + 9, '                   and not el.parent.previous_sibling))):\n')\n            lines.insert(i + 10, '        # first row, not headline, and:\n')\n            lines.insert(i + 11, '        # - the parent is table or\n')\n            lines.insert(i + 12, '        # - the parent is tbody at the beginning of a table.\n')\n            lines.insert(i + 13, '        # print empty headline above this row\n')\n            lines.insert(i + 14, '        overline += ": 1.4089190209703507e-06,
-   " + text + n + underline')\n            continue\n        # Print the line unchanged\n        print(line, end='')": 9.66406548680024e-08,
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-   "; return printer.doprint(expr, assign_to)'); exec(patched_source); print('Patched octave_code function with inline patch')": 5.248913999693464e-07,
-   "==": 4.424704363377961e-07,
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-   "A finite state machine strategy that starts in state 1 and transitions based on opponent's moves.": 1.222349835545053e-07,
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-   "tags,\n            params=query_params\n        )\n        return response": 2.8178380419407014e-06,
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-   "toil-wes-server": 4.461576899739444e-06,
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-   "update_server.py": 4.881968644091793e-07,
-   "url,": 3.743980615165967e-07,
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-   "uvicorn": 3.8384060608902395e-05,
-   "val": 7.931692266203456e-07,
-   "val.__class__": 1.4621974713431792e-06,
-   "val.crs": 2.9243949426863584e-06,
-   "valgrind": 7.5406933516723e-07,
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-   "validate_git_url.sh": 3.824208771205237e-06,
-   "valohai": 9.115582924981163e-06,
-   "value": 2.655682218488216e-07,
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-   "verification.sh": 7.812546674221859e-06,
-   "verify_nicolive.py": 1.8654676932708476e-07,
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-   "virtualenv": 3.0609616816911435e-05,
-   "vkplay\\.live": 2.878436709509319e-07,
-   "vyper": 1.5136128598922501e-05,
-   "w": 5.769367143248967e-05,
-   "w25g0011.hpc.itc.rwth-aachen.de": 1.6223915999052523e-06,
-   "watch": 2.8178380419407014e-06,
-   "wc": 0.00019771814785490355,
-   "wget": 0.0007236055863520736,
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-   "whereis": 1.0719480509047895e-05,
-   "which": 0.003031873606129561,
-   "whoami": 1.3781229767961355e-06,
-   "wily": 0.00012641297368518666,
-   "wily-filtered": 4.283113823749866e-06,
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-   "wq": 4.073248113921749e-05,
-   "write-zip": 5.08782591733445e-05,
-   "write_cache_to_file": 1.4052210707840768e-07,
-   "write_dataset.py": 1.5981767999066664e-06,
-   "write_gdrive.py": 1.381649620564473e-06,
-   "write_gdrive_final.py": 1.4967870889448457e-06,
-   "wscat": 6.369628069898284e-06,
-   "x": 1.8719903075829834e-07,
-   "x,": 5.353892279687333e-06,
-   "x-access-token": 1.0101683546579873e-06,
-   "x.dtype": 1.4089190209703507e-06,
-   "x1": 5.353892279687332e-07,
-   "x86_64": 1.6223915999052523e-06,
-   "x_squared": 2.8178380419407014e-06,
-   "x_val": 1.1513746838037276e-06,
-   "xargs": 0.011872162561123611,
-   "xcp_d": 4.43519098639782e-05,
-   "xeyes": 1.574674199908039e-06,
-   "xmin,": 1.4568414366496143e-06,
-   "xmldiff": 5.9619209522760415e-05,
-   "xmllint": 1.620323000441562e-05,
-   "xmlstarlet": 1.111185190123786e-05,
-   "xsel": 1.1143268620401865e-05,
-   "xxd": 0.00037970803283593696,
-   "xz,": 4.780260964006547e-07,
-   "y": 8.700536232671226e-05,
-   "y.dtype": 1.4089190209703507e-06,
-   "yapf": 4.7183862209426074e-05,
-   "yes": 3.6410686367540717e-05,
-   "yotta": 4.461576899739444e-06,
-   "your_api_key_here": 1.0926310774872107e-06,
-   "your_password_here": 1.0926310774872107e-06,
-   "yq": 2.038917526202171e-05,
-   "yum": 3.673107483299231e-05,
-   "zcat": 5.164760215459247e-06,
-   "zip": 7.650340589132871e-05,
-   "zipinfo": 3.557597266458903e-06,
-   "zoom_start": 1.9829230665508638e-06,
-   "zstd": 1.6431374134006208e-05,
-   "zstdcat": 1.5260055809207173e-05,
-   "{ print }": 1.4509193169884371e-07
+   "\n": 1.1330137650283231e-05,
+   "\n\n\n@staticmethod\ndef heatmap(data, labels=None, cmap='viridis', figsize=(10, 8), title='ANI Heatmap'):\n    ": 5.930937084500789e-08,
+   "\n\n        t = super(MetricTensor, self).lorentz_transform(transformation_matrix)\n        return MetricTensor(\n            t.tensor(), syms=self.syms, config=self.config, parent_metric=None\n        )": 5.977454238104717e-07,
+   "\n\n        t = super(MetricTensor, self).lorentz_transform(transformation_matrix)\n        return MetricTensor(\n            t.tensor(), syms=self.syms, config=self.config, parent_metric=self\n        )": 3.810627076791757e-07,
+   "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with ZipFile(fname, 'r') as zf:\n            zf.extractall(path=extract_dir, members=self.members)\n\n\nclass Untar(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+   "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with tarfile.open(fname, 'r') as tf:\n            tf.extractall(path=extract_dir, members=self.members)\n\nclass Decompress(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+   "\n\n    def __init__(self, method=auto, name=None):\n        self.method = method\n        self.name = name\n\n    def __call__(self, fname, action, pooch):\n        if self.name is None:\n            decompressed = fname + .decomp\n        else:\n            decompressed = os.path.join(os.path.dirname(fname), self.name)\n        if action in ('update', 'download') or not os.path.exists(decompressed):\n            get_logger().info(\n                Decompressing": 2.7218764834226833e-07,
+   "\n\n    def __init__(self, model):\n        if not isinstance(model, Model):\n            raise TypeError(model": 8.129337763822415e-08,
+   "\n\n    def __init__(self, url: URL) -> None:\n        self._url = url\n        warnings.warn(\n            RawURL": 1.2702090255972522e-06,
+   "\n        # Extract components\n        day = self._day\n        month = self._month\n        year = self._year\n        hour = self._hour\n        minute = self._minute\n\n        # Handle format specifiers\n        if not format_spec:\n            return str(self)\n\n        # Replace format codes\n        result = format_spec\n        result = result.replace('%-d', str(day))\n        result = result.replace('%d', f'{day:02d}')\n        result = result.replace('%-m', str(month))\n        result = result.replace('%m', f'{month:02d}')\n        result = result.replace('%Y', f'{year:04d}')\n        result = result.replace('%H:%M', f'{hour:02d}:{minute:02d}')\n\n        return result": 1.1635502524554982e-07,
+   "\n        # Read the source\n        pos = stream.tell()\n        source = stream.read()\n        stream.seek(pos)\n\n        # Parse the source\n        model = hy.models.Lazy()\n        for token in self.tokenize(stream, filename, skip_shebang):\n            model.append(token)\n\n        # Fill positions\n        self.fill_pos(model, (1, 0))\n\n        return model": 3.18658710254363e-07,
+   "\n        error_archives = To": 2.7218764834226833e-07,
+   "\n        if isinstance(state, int):\n            # If state is already an integer, return it directly\n            return state\n        else:\n            # Otherwise, get the state number from the state name\n            return self.model.get_cpds(variable).get_state_no(variable, state)\n\n    def _get_state_name(self, variable, state_no):\n        ": 8.129337763822415e-08,
+   "\n        if isinstance(state, int):\n            # If state is already an integer, return it directly\n            return state\n        else:\n            # Otherwise, get the state number from the state name\n            return self.model.get_cpds(variable).get_state_no(variable, state)\n\n    def _get_state_names(self, variable, state_nos):\n        ": 8.129337763822415e-08,
+   "\n        if not len(ground_truth_answers) == len(predicted_answers):\n            raise ValueError(The": 4.618941911262736e-07,
+   "\n        if self.options.get(\\'parse_block_html\\'):\n            return text\n        return escape(text)\n''')": 1.2292345409005668e-07,
+   "\n        if source_backend is None:\n            # Copy from S3 to local\n            source_client = self.client\n            source_bucket = self.bucket\n            source_key = source_path\n            dest_path = pathlib.Path(dest_path)\n            dest_path.parent.mkdir(parents=True, exist_ok=True)\n            \n            # Use boto3's copy_object to copy within S3, but for S3-to-local, use download_file\n            source_client.download_file(source_bucket, source_key, str(dest_path))\n        else:\n            # Copy from local to S3\n            if isinstance(source_backend, LocalFSStorage):\n                # Use boto3 to upload file to S3\n                source_client = self.client\n                source_client.upload_file(str(source_path), self.bucket, source_path)\n            else:\n                raise ValueError('Unsupported source backend')\n": 1.2194006645733623e-06,
+   "\n        if source_backend is None:\n            # Copy from local to S3\n            source_path = pathlib.Path(source_path)\n            dest_key = dest_path\n            \n            # Use boto3 to upload file to S3\n            self.client.upload_file(str(source_path), self.root.name, dest_key)\n        else:\n            # Copy from S3 to local\n            if isinstance(source_backend, S3Backend):\n                # Use boto3 to download file from S3\n                dest_path = pathlib.Path(dest_path)\n                dest_path.parent.mkdir(parents=True, exist_ok=True)\n                source_backend.client.download_file(source_backend.bucket, source_path, str(dest_path))\n            else:\n                raise ValueError('Unsupported source backend')\n": 1.2194006645733623e-06,
+   "\n        raise NotImplementedError\n\n\nclass Unzip(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+   "\n        return self._get_all_state_combinations(variables, state_names)\n\n    def _get_state_combinations_nos(self, variables, state_nos=None):\n        ": 8.129337763822415e-08,
+   "\n        return self._get_all_state_combinations_nos(variables, state_nos)\n\n    def _get_state_combinations_from_evidence(self, evidence):\n        ": 8.129337763822415e-08,
+   "\n        return self.converter.map_to_openapi_type(field_type)(cls)\n": 1.2702090255972522e-06,
+   "\n        return self.map_to_openapi_type(field_type)'); else: print(line, end='')": 1.1045295874758716e-07,
+   "\n        try:\n            self.client.copy_object(\n                CopySource={'Bucket': self.bucket, 'Key': source_key},\n                Bucket=self.bucket,\n                Key=dest_key\n            )\n        except Exception as e:\n            raise RuntimeError(f'Failed to copy S3 object: {e}')\n": 1.1725006390128483e-06,
+   "\n        try:\n            shutil.copy2(source_path, dest_path)\n        except Exception as e:\n            raise RuntimeError(f'Failed to copy local file: {e}')\n": 1.1725006390128483e-06,
+   "\n    # Get parents of the node\n    parents = set(model.get_parents(node))\n\n    # Get children of the node\n    children = set(model.get_children(node))\n\n    # Get other parents of children (i.e., parents of children excluding the node itself)\n    other_parents = set()\n    for child in children:\n        child_parents = set(model.get_parents(child))\n        other_parents.update(child_parents - {node})\n\n    # The Markov blanket is the union of parents, children, and other parents of children\n    markov_blanket = parents | children | other_parents\n\n    return markov_blanket": 1.2702090255972522e-06,
+   "\n    client = _compute_client_factory()\n    return _get_vmss_instance_view(client, resource_group_name, vm_scale_set_name, instance_id)": 2.931251597532121e-07,
+   "\n    fig, ax = plt.subplots(figsize=(8, 6))\n    im = ax.imshow(data, cmap=cmap, interpolation='nearest')\n    plt.colorbar(im)\n    if labels:\n        ax.set_xticks(range(len(labels)))\n        ax.set_yticks(range(len(labels)))\n        ax.set_xticklabels(labels)\n        ax.set_yticklabels(labels)\n    ax.set_title(title)\n    plt.tight_layout()\n    plt.show()\n\n\ndef distribution(data, title='ANI Distribution', bins=50):\n    ": 5.930937084500789e-08,
+   "\n    fig, ax = plt.subplots(figsize=figsize)\n    ax.hist(data, bins=bins, color=color, alpha=0.7)\n\n    # Set labels\n    ax.set_xlabel('ANI Value')\n    ax.set_ylabel('Frequency')\n    ax.set_title(title)\n\n    # Tight layout\n    fig.tight_layout()\n\n    return fig, ax\n": 5.930937084500789e-08,
+   "\n    fig, ax = plt.subplots(figsize=figsize)\n    im = ax.imshow(data, cmap=cmap, aspect='auto')\n\n    # Set labels\n    if labels:\n        ax.set_xticks(np.arange(len(labels)))\n        ax.set_yticks(np.arange(len(labels)))\n        ax.set_xticklabels(labels)\n        ax.set_yticklabels(labels)\n\n    # Rotate labels\n    plt.setp(ax.get_xticklabels(), rotation=45, ha='right', rotation_mode='anchor')\n\n    # Add colorbar\n    cbar = fig.colorbar(im, ax=ax)\n    cbar.ax.set_ylabel('ANI Value')\n\n    # Set title\n    ax.set_title(title)\n\n    # Tight layout\n    fig.tight_layout()\n\n    return fig, ax\n\n\n@staticmethod\ndef distribution(data, bins=50, color='blue', figsize=(10, 6), title='ANI Distribution'):\n    ": 5.930937084500789e-08,
+   "\n    from .core import Array\n    from .utils import meta_from_array\n    import numpy as np\n    \n    if meta is None:\n        meta = np.empty(shape, dtype=dtype)\n    \n    if chunks is None:\n        chunks = shape\n    \n    return Array(\n        name=name,\n        shape=shape,\n        dtype=dtype,\n        chunks=chunks,\n        meta=meta,\n    )": 1.6389793878674224e-07,
+   "\n    http_code = httpstatus.CONFLICT\n": 2.1775011867381466e-06,
+   "\n    if is_pandas_like(df):\n        return df.convert_dtypes()\n    return df\n": 1.2194006645733623e-06,
+   "\n    name = 'matrix_stats'\n": 2.7713651467576416e-06,
+   "\n    plt.figure(figsize=(8, 6))\n    plt.hist(data.values.flatten(), bins=bins, color='skyblue', edgecolor='black')\n    plt.title(title)\n    plt.xlabel('ANI Value')\n    plt.ylabel('Frequency')\n    plt.tight_layout()\n    plt.show()\n": 5.930937084500789e-08,
+   "\n    plugin = MarshmallowPlugin()\n    return plugin.map_to_openapi_type(field_type)\n": 5.348248528830535e-07,
+   "\n    return e\n": 8.129337763822415e-08,
+   "\n    return self.converter.map_to_openapi_type(field_type)\n": 1.1725006390128483e-06,
+   "\ncp": 9.67778305216954e-07,
+   "\nprintf": 9.67778305216954e-07,
+   "\npython": 3.7890981102562105e-06,
+   "\ntail": 9.67778305216954e-07,
+   "                elif char == ": 8.172926706255778e-08,
+   "                message += formatter.format(w=warning)": 5.751889927232841e-07,
+   "            return html + >": 1.9053135383958786e-07,
+   "        # Placeholder for pipeline registration": 9.833876327204534e-08,
+   "        result.setdefault('typedefs', 0)": 7.938806409982826e-08,
+   "        return func": 9.833876327204534e-08,
+   "        return self.__dict__": 8.861923434399434e-08,
+   "        self.__dict__.update(state)": 8.861923434399434e-08,
+   "    def __getstate__(self):": 8.861923434399434e-08,
+   "    def __setstate__(self, state):": 8.861923434399434e-08,
+   "    def decorator(func: callable) -> callable:": 9.833876327204534e-08,
+   "    def resolve_type(self, string, result):  # recursive": 7.938806409982826e-08,
+   "    qs = ": 2.697789080914518e-07,
+   "    return decorator": 9.833876327204534e-08,
+   "    try:\\n        filename = to_native_str(content_disposition, encoding=encoding).split(\\\\": 1.2917379921327988e-07,
+   " + ": 2.571793155379882e-06,
+   " + n\n            overline += ": 5.502710580204703e-08,
+   " + n\n        elif (not el.previous_sibling\n              and (el.parent.name == table\n                   or (el.parent.name == tbody\n                       and not el.parent.previous_sibling))):\n            # first row, not headline, and:\n            # - the parent is table or\n            # - the parent is tbody at the beginning of a table.\n            # print empty headline above this row\n            overline += ": 5.502710580204703e-08,
+   " + n\n        return overline + ": 5.502710580204703e-08,
+   " + n\n')\n            break\n\n# Write back\nwith open('__init__.py', 'w') as f: f.writelines(lines)": 8.022372793245803e-07,
+   " + n\n')\n            lines.insert(i + 15, '        overline += ": 8.022372793245803e-07,
+   " + n\n')\n            lines.insert(i + 6, '    elif (not el.previous_sibling\n')\n            lines.insert(i + 7, '          and (el.parent.name == table\n')\n            lines.insert(i + 8, '               or (el.parent.name == tbody\n')\n            lines.insert(i + 9, '                   and not el.parent.previous_sibling))):\n')\n            lines.insert(i + 10, '        # first row, not headline, and:\n')\n            lines.insert(i + 11, '        # - the parent is table or\n')\n            lines.insert(i + 12, '        # - the parent is tbody at the beginning of a table.\n')\n            lines.insert(i + 13, '        # print empty headline above this row\n')\n            lines.insert(i + 14, '        overline += ": 8.022372793245803e-07,
+   " + text + n + underline')\n            continue\n        # Print the line unchanged\n        print(line, end='')": 5.502710580204703e-08,
+   " Lazy init of custom DDB clients. ": 1.917296642410947e-07,
+   " and s.value.strip().replace(": 1.1861874169001577e-07,
+   " in inflected:\n            parts = inflected.split(": 8.563206914138779e-08,
+   " in inflected:\\n')\n        new_lines.append('                parts = inflected.split(": 8.66051608361763e-08,
+   " or token == ": 1.6415008946179878e-06,
+   " { next } \n": 1.652304423541141e-07,
+   " || ": 3.810627076791757e-07,
+   "!bash": 3.350001825750995e-07,
+   "!cat": 1.4470175626944557e-05,
+   "!cd": 3.678006644884851e-06,
+   "!cp": 7.073089701701636e-08,
+   "!echo": 1.3626331836193778e-05,
+   "!exit": 3.350001825750995e-07,
+   "!find": 6.179882209643369e-06,
+   "!grep": 4.188252845144524e-06,
+   "!ipython": 8.979994685280399e-06,
+   "!jupyter-console": 5.751889927232841e-07,
+   "!ls": 1.8963426056815193e-06,
+   "!mkdir": 3.1107159810544953e-07,
+   "!nano": 7.621254153583514e-07,
+   "!pip": 9.10274879845316e-06,
+   "!pkill": 5.751889927232841e-07,
+   "!printf": 4.722866633078126e-06,
+   "!ps": 5.751889927232841e-07,
+   "!pstree": 5.751889927232841e-07,
+   "!pwd": 3.350001825750995e-07,
+   "!python": 9.814020649250645e-06,
+   "!python3": 5.718552866426749e-06,
+   "!sed": 1.7286587365206637e-05,
+   "!touch": 3.1107159810544953e-07,
+   "\") if \"and: and:": 1.4179077495039095e-06,
+   "\");}1": 6.804691208556708e-08,
+   "\", \"and: ": 1.4179077495039095e-06,
+   "\"PASSWORD\":": 1.4798551754531092e-07,
+   "\"dps\":": 1.722317322843732e-07,
+   "\"func_path_generator\":": 3.018318476666738e-07,
+   "%-d:": 1.1635502524554982e-07,
+   "%-m:": 1.1635502524554982e-07,
+   "%:": 8.563206914138779e-08,
+   "%H:%M:": 1.1635502524554982e-07,
+   "%Y:": 1.1635502524554982e-07,
+   "%autoreload": 2.4388013291467246e-06,
+   "%config": 4.7263591650130315e-07,
+   "%d:": 1.1635502524554982e-07,
+   "%load_ext": 2.6213463388133955e-06,
+   "%m:": 1.1635502524554982e-07,
+   "%paste": 2.5404180511945044e-06,
+   "%run": 3.387224068259339e-06,
+   "%s": 1.4516674578254313e-07,
+   "%version": 1.0887505933690733e-06,
+   "', start='PROGRAM', parser='earley')": 7.816670926752321e-07,
+   "(from": 2.1775011867381466e-07,
+   ")": 1.3254355049710459e-07,
+   ")\n            f.write(": 4.900142373184918e-06,
+   ")\n            prefix = orig.split(": 8.563206914138779e-08,
+   ")\n        new_lines.append(": 5.509340351988082e-06,
+   ") (setv quotechar = \") (setv quoting csv.QUOTE-MINIMAL))'))": 6.59848844466105e-08,
+   ") (setv quotechar = \\\") (setv quoting csv.QUOTE-MINIMAL))'))": 1.31969768893221e-07,
+   ") (setv quotechar = \\\") (setv quoting csv.QUOTE-MINIMAL))'; hy.compile(hy.read_string(repr(code)))": 6.59848844466105e-08,
+   ") and not statement.endswith(": 6.627177524855229e-08,
+   ") f.write(": 2.796790515076519e-07,
+   ") or token.endswith(": 5.011235607835734e-07,
+   "):": 6.627177524855229e-08,
+   ")|": 4.371436344696959e-06,
+   "+": 1.0841824090612311e-06,
+   "+, sql) if s.strip() !=  and s.strip() != ": 2.135137350420284e-06,
+   ",\n    ": 1.8872036008732292e-06,
+   ",\n        ": 4.572752492150108e-07,
+   ",\n    tables=tables\n)\nprint(result)": 2.822686723549449e-07,
+   ", ": 7.024197376574667e-08,
+   ", <>).split(": 6.627177524855229e-08,
+   ", set())": 1.3254355049710459e-06,
+   ",wq": 2.1620579159102167e-07,
+   "...": 4.4996334486101926e-07,
+   ".exit": 2.7769134253297287e-06,
+   ".join(errors)}\")": 9.526567691979392e-07,
+   ".join(errors)}\")\\\n": 9.526567691979392e-07,
+   ".join(errors)}\\\")\"; next } { print }": 9.526567691979392e-07,
+   ".join(qs_strings)": 2.697789080914518e-07,
+   ".join(qs_strings) # replaced with direct rebuild|g": 1.8038471369428435e-07,
+   ".join(qs_strings) - replaced with proper logic|g": 1.665847902422626e-07,
+   ".join(qs_strings)|# qs = ": 3.4696950393654695e-07,
+   ".join(qs_strings)|g": 8.605237981153566e-07,
+   ".join(qs_strings)|qs = ": 4.997543707267878e-07,
+   ".mean().reset_index(0)": 6.944195128549898e-08,
+   ".open": 3.302543466552856e-06,
+   ".tables": 6.036636953333476e-07,
+   ".wq": 8.194896939337112e-08,
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+   ":Parameters:": 1.1725006390128484e-07,
+   ":Returns:": 1.1725006390128484e-07,
+   ":\\n'); f.write('        self.context.add_to_long_function_name(": 1.1725006390128484e-07,
+   ":\\n'); f.write('        self.context.add_to_long_function_name(\" \" + token)\\n'); else: f.write(line);": 7.03500383407709e-07,
+   ":grep": 3.3872240682593394e-07,
+   ":param": 3.1343586452314134e-05,
+   ":paste": 3.837274818587504e-06,
+   ":q": 6.259757004996726e-08,
+   ":q!": 1.9053135383958784e-06,
+   ":raises:": 2.0323344409556035e-06,
+   ":return:": 7.126284660635799e-06,
+   ":returns:": 5.20654174211017e-06,
+   ":rtype:": 4.9882409697360435e-06,
+   ":set": 4.47225455509528e-06,
+   ":type": 1.0065191096165975e-05,
+   ":wq": 6.247368595618339e-05,
+   "; return printer.doprint(expr, assign_to)'); exec(patched_source); print('Patched octave_code function with inline patch')": 2.988727119052358e-07,
+   "==": 2.519422860688765e-07,
+   "=======": 1.960451229217624e-07,
+   "==========": 1.960451229217624e-07,
+   "@auto_attr": 1.1375006199378378e-07,
+   "@cacheit": 2.113210394318407e-06,
+   "@classmethod": 2.0880148365982228e-07,
+   "@end)\nureg.define(@context": 9.833876327204534e-07,
+   "@end)\nureg.enable_contexts(\"c1\")\nureg.enable_contexts(\"c2\")\nureg.enable_contexts(\"c3\")": 4.916938163602267e-07,
+   "@functools.wraps": 2.478456635311712e-07,
+   "@property": 2.392048354044317e-06,
+   "@staticmethod": 5.89489271547896e-07,
+   "A": 6.344756812266146e-06,
+   "A finite state machine strategy that starts in state 1 and transitions based on opponent's moves.": 6.960049455327409e-08,
+   "AKIA1234567890": 1.959751068064332e-06,
+   "AKIAIOSFODNN7EXAMPLE": 2.2324885904436557e-06,
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+   "Abstract": 8.129337763822415e-08,
+   "Additional": 1.2509214962057682e-06,
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+   "Arcanine": 3.319602535136195e-07,
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+   "AttributeError:": 2.1620579159102167e-07,
+   "Attributes": 1.1249083621525481e-07,
+   "BTreeFolder2.py": 9.833876327204534e-07,
+   "Bandwidth": 7.275660289817197e-08,
+   "Base": 5.775467463155643e-07,
+   "Base class for scopes.": 1.3856825733788206e-07,
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+   "Colormap": 1.1861874169001577e-07,
+   "Colors": 7.275660289817197e-08,
+   "Column": 1.1290746894197797e-06,
+   "Column {column.name} has no non-NaN values (all are NaN).": 9.496889911007493e-08,
+   "Column {column.name} has only one value: '{value}'.": 9.496889911007493e-08,
+   "Configuration": 1.1770276685071064e-07,
+   "Configure": 3.3747250864576443e-07,
+   "ConnectionError,": 8.66051608361763e-08,
+   "Contexts": 4.909020388781651e-08,
+   "Convert": 2.2090591749517432e-07,
+   "Convert marshmallow Enum field to OpenAPI schema properties.": 6.084833655555699e-08,
+   "Copy": 2.4388013291467246e-06,
+   "Ctrl+K": 1.5648808309936115e-06,
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+   "DestinationBaseType": 9.265962496758071e-08,
+   "Dictionary": 8.562188160497584e-07,
+   "Discharge at 1C until 3 V,": 1.7621396886898297e-07,
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+   "E.g.,": 8.468060170648348e-07,
+   "EEEE:": 1.5166674932504505e-07,
+   "END_OF_UTILS_FILE_1234567890_ABCDEF": 1.3856825733788206e-07,
+   "EOF": 1.7185420532633448e-05,
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+   "Execute": 3.350001825750995e-07,
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+   "FUNCTION_PARSERS": 4.536460805704472e-08,
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+   "FieldConverter,": 1.960451229217624e-07,
+   "Figure": 1.9137534458818776e-07,
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+   "GET": 1.2045313582239762e-05,
+   "Generate": 2.3723748338003155e-07,
+   "Get": 2.991105570369927e-06,
+   "Gets the configuration loader for path according to file extension.": 6.737020246261669e-07,
+   "GoldenRatio": 6.687035902499083e-06,
+   "GramSchmidt": 1.3856825733788208e-06,
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+   "Hello": 2.867540375594893e-06,
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+   "Jalil,": 1.2519514009993452e-07,
+   "Jane": 3.835619981654069e-06,
+   "Karaamat,": 1.2519514009993452e-07,
+   "Karam,": 1.2519514009993452e-07,
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+   "NR == 105 { in_block = 1; next } \n": 8.261522117705705e-08,
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+   "Notes:\\n": 1.2702090255972522e-06,
+   "Number": 3.4542532512458385e-07,
+   "ORDER": 1.82545009666671e-07,
+   "Obs": 1.1770276685071064e-07,
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+   "Original": 1.2649384487275542e-07,
+   "PARAMETERS:": 1.2649384487275542e-07,
+   "PASSWORD_HERE": 8.239193679549745e-07,
+   "POSITIONAL:": 1.4621111086011536e-07,
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+   "Request": 3.4252827656555117e-07,
+   "Return a dictionary of properties from field metadata\n": 6.084833655555699e-08,
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+   "ValueError.": 2.7218764834226833e-07,
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+   "Wrap a generic pandas method to ensure it returns a GeoSeries and preserves CRS if requested.": 8.325739831645855e-07,
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+   "\\n\np2 = SimpleHeuristicsPlayer(\n    battle_format='gen8nationaldexag',\n    team=opponent_team,\n    max_concurrent_battles=20,\n    log_level=40,\n)\nprint('Success: Player created without error.')": 2.0055931983114508e-07,
+   "\\n        self.context.add_to_long_function_name(": 7.03500383407709e-07,
+   "\\n    node = value\\n    while node is not None:\\n        if hasattr(node, parent):\\n            return node.parent\\n        node = node.parent\\n    return None\\n')": 1.0548448655478912e-07,
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     "trajectories": 0,
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    "environment": {
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     "types": {
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+     "AgentSetupTimeoutError": 1,
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    "tools": {
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     },
     "mark_task_complete": {
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    },
-   "tool_steps": 549566,
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    "tool_steps_without_output": 0,
-   "tool_steps_with_error_text": 226210,
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+   "tool_steps_with_error_text": 404555,
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    "terminations": {
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-    "not_recorded": 14029,
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-    "session_ended": 49,
-    "task_complete": 16327,
-    "task_memory_limit": 10,
-    "task_timeout": 2244,
-    "verifier_error": 1341
+    "environment_error": 38,
+    "other_error": 1462,
+    "session_ended": 83,
+    "task_complete": 28520,
+    "task_memory_limit": 24,
+    "task_timeout": 4060,
+    "verifier_error": 29
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    "command_distribution": {
-    "\n": 1.989841018001075e-05,
-    "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with ZipFile(fname, 'r') as zf:\n            zf.extractall(path=extract_dir, members=self.members)\n\n\nclass Untar(ExtractorProcessor):\n    ": 4.780260964006547e-07,
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-    "\n    from .core import Array\n    from .utils import meta_from_array\n    import numpy as np\n    \n    if meta is None:\n        meta = np.empty(shape, dtype=dtype)\n    \n    if chunks is None:\n        chunks = shape\n    \n    return Array(\n        name=name,\n        shape=shape,\n        dtype=dtype,\n        chunks=chunks,\n        meta=meta,\n    )": 2.878436709509319e-07,
-    "\n    http_code = httpstatus.CONFLICT\n": 3.824208771205237e-06,
-    "\n    plugin = MarshmallowPlugin()\n    return plugin.map_to_openapi_type(field_type)\n": 9.39279347313567e-07,
-    "\n    return e\n": 1.427704607916622e-07,
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-    " + n\n')\n            lines.insert(i + 15, '        overline += ": 1.4089190209703507e-06,
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-    " + text + n + underline')\n            continue\n        # Print the line unchanged\n        print(line, end='')": 9.66406548680024e-08,
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-    "whoami": 1.3781229767961355e-06,
-    "wily": 0.00012641297368518666,
-    "wily-filtered": 4.283113823749866e-06,
-    "wn": 5.350896104724138e-06,
-    "wq": 4.073248113921749e-05,
-    "write-zip": 5.08782591733445e-05,
-    "write_cache_to_file": 1.4052210707840768e-07,
-    "write_dataset.py": 1.5981767999066664e-06,
-    "write_gdrive.py": 1.381649620564473e-06,
-    "write_gdrive_final.py": 1.4967870889448457e-06,
-    "wscat": 6.369628069898284e-06,
-    "x": 1.8719903075829834e-07,
-    "x,": 5.353892279687333e-06,
-    "x-access-token": 1.0101683546579873e-06,
-    "x.dtype": 1.4089190209703507e-06,
-    "x1": 5.353892279687332e-07,
-    "x86_64": 1.6223915999052523e-06,
-    "x_squared": 2.8178380419407014e-06,
-    "x_val": 1.1513746838037276e-06,
-    "xargs": 0.011872162561123611,
-    "xcp_d": 4.43519098639782e-05,
-    "xeyes": 1.574674199908039e-06,
-    "xmin,": 1.4568414366496143e-06,
-    "xmldiff": 5.9619209522760415e-05,
-    "xmllint": 1.620323000441562e-05,
-    "xmlstarlet": 1.111185190123786e-05,
-    "xsel": 1.1143268620401865e-05,
-    "xxd": 0.00037970803283593696,
-    "xz,": 4.780260964006547e-07,
-    "y": 8.700536232671226e-05,
-    "y.dtype": 1.4089190209703507e-06,
-    "yapf": 4.7183862209426074e-05,
-    "yes": 3.6410686367540717e-05,
-    "yotta": 4.461576899739444e-06,
-    "your_api_key_here": 1.0926310774872107e-06,
-    "your_password_here": 1.0926310774872107e-06,
-    "yq": 2.038917526202171e-05,
-    "yum": 3.673107483299231e-05,
-    "zcat": 5.164760215459247e-06,
-    "zip": 7.650340589132871e-05,
-    "zipinfo": 3.557597266458903e-06,
-    "zoom_start": 1.9829230665508638e-06,
-    "zstd": 1.6431374134006208e-05,
-    "zstdcat": 1.5260055809207173e-05,
-    "{ print }": 1.4509193169884371e-07
+    "\n": 1.1330137650283231e-05,
+    "\n\n\n@staticmethod\ndef heatmap(data, labels=None, cmap='viridis', figsize=(10, 8), title='ANI Heatmap'):\n    ": 5.930937084500789e-08,
+    "\n\n        t = super(MetricTensor, self).lorentz_transform(transformation_matrix)\n        return MetricTensor(\n            t.tensor(), syms=self.syms, config=self.config, parent_metric=None\n        )": 5.977454238104717e-07,
+    "\n\n        t = super(MetricTensor, self).lorentz_transform(transformation_matrix)\n        return MetricTensor(\n            t.tensor(), syms=self.syms, config=self.config, parent_metric=self\n        )": 3.810627076791757e-07,
+    "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with ZipFile(fname, 'r') as zf:\n            zf.extractall(path=extract_dir, members=self.members)\n\n\nclass Untar(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+    "\n\n    def __init__(self, members=None, extract_dir=None):\n        super().__init__(members=members, extract_dir=extract_dir)\n\n    def _extract_file(self, fname, extract_dir):\n        with tarfile.open(fname, 'r') as tf:\n            tf.extractall(path=extract_dir, members=self.members)\n\nclass Decompress(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+    "\n\n    def __init__(self, method=auto, name=None):\n        self.method = method\n        self.name = name\n\n    def __call__(self, fname, action, pooch):\n        if self.name is None:\n            decompressed = fname + .decomp\n        else:\n            decompressed = os.path.join(os.path.dirname(fname), self.name)\n        if action in ('update', 'download') or not os.path.exists(decompressed):\n            get_logger().info(\n                Decompressing": 2.7218764834226833e-07,
+    "\n\n    def __init__(self, model):\n        if not isinstance(model, Model):\n            raise TypeError(model": 8.129337763822415e-08,
+    "\n\n    def __init__(self, url: URL) -> None:\n        self._url = url\n        warnings.warn(\n            RawURL": 1.2702090255972522e-06,
+    "\n        # Extract components\n        day = self._day\n        month = self._month\n        year = self._year\n        hour = self._hour\n        minute = self._minute\n\n        # Handle format specifiers\n        if not format_spec:\n            return str(self)\n\n        # Replace format codes\n        result = format_spec\n        result = result.replace('%-d', str(day))\n        result = result.replace('%d', f'{day:02d}')\n        result = result.replace('%-m', str(month))\n        result = result.replace('%m', f'{month:02d}')\n        result = result.replace('%Y', f'{year:04d}')\n        result = result.replace('%H:%M', f'{hour:02d}:{minute:02d}')\n\n        return result": 1.1635502524554982e-07,
+    "\n        # Read the source\n        pos = stream.tell()\n        source = stream.read()\n        stream.seek(pos)\n\n        # Parse the source\n        model = hy.models.Lazy()\n        for token in self.tokenize(stream, filename, skip_shebang):\n            model.append(token)\n\n        # Fill positions\n        self.fill_pos(model, (1, 0))\n\n        return model": 3.18658710254363e-07,
+    "\n        error_archives = To": 2.7218764834226833e-07,
+    "\n        if isinstance(state, int):\n            # If state is already an integer, return it directly\n            return state\n        else:\n            # Otherwise, get the state number from the state name\n            return self.model.get_cpds(variable).get_state_no(variable, state)\n\n    def _get_state_name(self, variable, state_no):\n        ": 8.129337763822415e-08,
+    "\n        if isinstance(state, int):\n            # If state is already an integer, return it directly\n            return state\n        else:\n            # Otherwise, get the state number from the state name\n            return self.model.get_cpds(variable).get_state_no(variable, state)\n\n    def _get_state_names(self, variable, state_nos):\n        ": 8.129337763822415e-08,
+    "\n        if not len(ground_truth_answers) == len(predicted_answers):\n            raise ValueError(The": 4.618941911262736e-07,
+    "\n        if self.options.get(\\'parse_block_html\\'):\n            return text\n        return escape(text)\n''')": 1.2292345409005668e-07,
+    "\n        if source_backend is None:\n            # Copy from S3 to local\n            source_client = self.client\n            source_bucket = self.bucket\n            source_key = source_path\n            dest_path = pathlib.Path(dest_path)\n            dest_path.parent.mkdir(parents=True, exist_ok=True)\n            \n            # Use boto3's copy_object to copy within S3, but for S3-to-local, use download_file\n            source_client.download_file(source_bucket, source_key, str(dest_path))\n        else:\n            # Copy from local to S3\n            if isinstance(source_backend, LocalFSStorage):\n                # Use boto3 to upload file to S3\n                source_client = self.client\n                source_client.upload_file(str(source_path), self.bucket, source_path)\n            else:\n                raise ValueError('Unsupported source backend')\n": 1.2194006645733623e-06,
+    "\n        if source_backend is None:\n            # Copy from local to S3\n            source_path = pathlib.Path(source_path)\n            dest_key = dest_path\n            \n            # Use boto3 to upload file to S3\n            self.client.upload_file(str(source_path), self.root.name, dest_key)\n        else:\n            # Copy from S3 to local\n            if isinstance(source_backend, S3Backend):\n                # Use boto3 to download file from S3\n                dest_path = pathlib.Path(dest_path)\n                dest_path.parent.mkdir(parents=True, exist_ok=True)\n                source_backend.client.download_file(source_backend.bucket, source_path, str(dest_path))\n            else:\n                raise ValueError('Unsupported source backend')\n": 1.2194006645733623e-06,
+    "\n        raise NotImplementedError\n\n\nclass Unzip(ExtractorProcessor):\n    ": 2.7218764834226833e-07,
+    "\n        return self._get_all_state_combinations(variables, state_names)\n\n    def _get_state_combinations_nos(self, variables, state_nos=None):\n        ": 8.129337763822415e-08,
+    "\n        return self._get_all_state_combinations_nos(variables, state_nos)\n\n    def _get_state_combinations_from_evidence(self, evidence):\n        ": 8.129337763822415e-08,
+    "\n        return self.converter.map_to_openapi_type(field_type)(cls)\n": 1.2702090255972522e-06,
+    "\n        return self.map_to_openapi_type(field_type)'); else: print(line, end='')": 1.1045295874758716e-07,
+    "\n        try:\n            self.client.copy_object(\n                CopySource={'Bucket': self.bucket, 'Key': source_key},\n                Bucket=self.bucket,\n                Key=dest_key\n            )\n        except Exception as e:\n            raise RuntimeError(f'Failed to copy S3 object: {e}')\n": 1.1725006390128483e-06,
+    "\n        try:\n            shutil.copy2(source_path, dest_path)\n        except Exception as e:\n            raise RuntimeError(f'Failed to copy local file: {e}')\n": 1.1725006390128483e-06,
+    "\n    # Get parents of the node\n    parents = set(model.get_parents(node))\n\n    # Get children of the node\n    children = set(model.get_children(node))\n\n    # Get other parents of children (i.e., parents of children excluding the node itself)\n    other_parents = set()\n    for child in children:\n        child_parents = set(model.get_parents(child))\n        other_parents.update(child_parents - {node})\n\n    # The Markov blanket is the union of parents, children, and other parents of children\n    markov_blanket = parents | children | other_parents\n\n    return markov_blanket": 1.2702090255972522e-06,
+    "\n    client = _compute_client_factory()\n    return _get_vmss_instance_view(client, resource_group_name, vm_scale_set_name, instance_id)": 2.931251597532121e-07,
+    "\n    fig, ax = plt.subplots(figsize=(8, 6))\n    im = ax.imshow(data, cmap=cmap, interpolation='nearest')\n    plt.colorbar(im)\n    if labels:\n        ax.set_xticks(range(len(labels)))\n        ax.set_yticks(range(len(labels)))\n        ax.set_xticklabels(labels)\n        ax.set_yticklabels(labels)\n    ax.set_title(title)\n    plt.tight_layout()\n    plt.show()\n\n\ndef distribution(data, title='ANI Distribution', bins=50):\n    ": 5.930937084500789e-08,
+    "\n    fig, ax = plt.subplots(figsize=figsize)\n    ax.hist(data, bins=bins, color=color, alpha=0.7)\n\n    # Set labels\n    ax.set_xlabel('ANI Value')\n    ax.set_ylabel('Frequency')\n    ax.set_title(title)\n\n    # Tight layout\n    fig.tight_layout()\n\n    return fig, ax\n": 5.930937084500789e-08,
+    "\n    fig, ax = plt.subplots(figsize=figsize)\n    im = ax.imshow(data, cmap=cmap, aspect='auto')\n\n    # Set labels\n    if labels:\n        ax.set_xticks(np.arange(len(labels)))\n        ax.set_yticks(np.arange(len(labels)))\n        ax.set_xticklabels(labels)\n        ax.set_yticklabels(labels)\n\n    # Rotate labels\n    plt.setp(ax.get_xticklabels(), rotation=45, ha='right', rotation_mode='anchor')\n\n    # Add colorbar\n    cbar = fig.colorbar(im, ax=ax)\n    cbar.ax.set_ylabel('ANI Value')\n\n    # Set title\n    ax.set_title(title)\n\n    # Tight layout\n    fig.tight_layout()\n\n    return fig, ax\n\n\n@staticmethod\ndef distribution(data, bins=50, color='blue', figsize=(10, 6), title='ANI Distribution'):\n    ": 5.930937084500789e-08,
+    "\n    from .core import Array\n    from .utils import meta_from_array\n    import numpy as np\n    \n    if meta is None:\n        meta = np.empty(shape, dtype=dtype)\n    \n    if chunks is None:\n        chunks = shape\n    \n    return Array(\n        name=name,\n        shape=shape,\n        dtype=dtype,\n        chunks=chunks,\n        meta=meta,\n    )": 1.6389793878674224e-07,
+    "\n    http_code = httpstatus.CONFLICT\n": 2.1775011867381466e-06,
+    "\n    if is_pandas_like(df):\n        return df.convert_dtypes()\n    return df\n": 1.2194006645733623e-06,
+    "\n    name = 'matrix_stats'\n": 2.7713651467576416e-06,
+    "\n    plt.figure(figsize=(8, 6))\n    plt.hist(data.values.flatten(), bins=bins, color='skyblue', edgecolor='black')\n    plt.title(title)\n    plt.xlabel('ANI Value')\n    plt.ylabel('Frequency')\n    plt.tight_layout()\n    plt.show()\n": 5.930937084500789e-08,
+    "\n    plugin = MarshmallowPlugin()\n    return plugin.map_to_openapi_type(field_type)\n": 5.348248528830535e-07,
+    "\n    return e\n": 8.129337763822415e-08,
+    "\n    return self.converter.map_to_openapi_type(field_type)\n": 1.1725006390128483e-06,
+    "\ncp": 9.67778305216954e-07,
+    "\nprintf": 9.67778305216954e-07,
+    "\npython": 3.7890981102562105e-06,
+    "\ntail": 9.67778305216954e-07,
+    "                elif char == ": 8.172926706255778e-08,
+    "                message += formatter.format(w=warning)": 5.751889927232841e-07,
+    "            return html + >": 1.9053135383958786e-07,
+    "        # Placeholder for pipeline registration": 9.833876327204534e-08,
+    "        result.setdefault('typedefs', 0)": 7.938806409982826e-08,
+    "        return func": 9.833876327204534e-08,
+    "        return self.__dict__": 8.861923434399434e-08,
+    "        self.__dict__.update(state)": 8.861923434399434e-08,
+    "    def __getstate__(self):": 8.861923434399434e-08,
+    "    def __setstate__(self, state):": 8.861923434399434e-08,
+    "    def decorator(func: callable) -> callable:": 9.833876327204534e-08,
+    "    def resolve_type(self, string, result):  # recursive": 7.938806409982826e-08,
+    "    qs = ": 2.697789080914518e-07,
+    "    return decorator": 9.833876327204534e-08,
+    "    try:\\n        filename = to_native_str(content_disposition, encoding=encoding).split(\\\\": 1.2917379921327988e-07,
+    " + ": 2.571793155379882e-06,
+    " + n\n            overline += ": 5.502710580204703e-08,
+    " + n\n        elif (not el.previous_sibling\n              and (el.parent.name == table\n                   or (el.parent.name == tbody\n                       and not el.parent.previous_sibling))):\n            # first row, not headline, and:\n            # - the parent is table or\n            # - the parent is tbody at the beginning of a table.\n            # print empty headline above this row\n            overline += ": 5.502710580204703e-08,
+    " + n\n        return overline + ": 5.502710580204703e-08,
+    " + n\n')\n            break\n\n# Write back\nwith open('__init__.py', 'w') as f: f.writelines(lines)": 8.022372793245803e-07,
+    " + n\n')\n            lines.insert(i + 15, '        overline += ": 8.022372793245803e-07,
+    " + n\n')\n            lines.insert(i + 6, '    elif (not el.previous_sibling\n')\n            lines.insert(i + 7, '          and (el.parent.name == table\n')\n            lines.insert(i + 8, '               or (el.parent.name == tbody\n')\n            lines.insert(i + 9, '                   and not el.parent.previous_sibling))):\n')\n            lines.insert(i + 10, '        # first row, not headline, and:\n')\n            lines.insert(i + 11, '        # - the parent is table or\n')\n            lines.insert(i + 12, '        # - the parent is tbody at the beginning of a table.\n')\n            lines.insert(i + 13, '        # print empty headline above this row\n')\n            lines.insert(i + 14, '        overline += ": 8.022372793245803e-07,
+    " + text + n + underline')\n            continue\n        # Print the line unchanged\n        print(line, end='')": 5.502710580204703e-08,
+    " Lazy init of custom DDB clients. ": 1.917296642410947e-07,
+    " and s.value.strip().replace(": 1.1861874169001577e-07,
+    " in inflected:\n            parts = inflected.split(": 8.563206914138779e-08,
+    " in inflected:\\n')\n        new_lines.append('                parts = inflected.split(": 8.66051608361763e-08,
+    " or token == ": 1.6415008946179878e-06,
+    " { next } \n": 1.652304423541141e-07,
+    " || ": 3.810627076791757e-07,
+    "!bash": 3.350001825750995e-07,
+    "!cat": 1.4470175626944557e-05,
+    "!cd": 3.678006644884851e-06,
+    "!cp": 7.073089701701636e-08,
+    "!echo": 1.3626331836193778e-05,
+    "!exit": 3.350001825750995e-07,
+    "!find": 6.179882209643369e-06,
+    "!grep": 4.188252845144524e-06,
+    "!ipython": 8.979994685280399e-06,
+    "!jupyter-console": 5.751889927232841e-07,
+    "!ls": 1.8963426056815193e-06,
+    "!mkdir": 3.1107159810544953e-07,
+    "!nano": 7.621254153583514e-07,
+    "!pip": 9.10274879845316e-06,
+    "!pkill": 5.751889927232841e-07,
+    "!printf": 4.722866633078126e-06,
+    "!ps": 5.751889927232841e-07,
+    "!pstree": 5.751889927232841e-07,
+    "!pwd": 3.350001825750995e-07,
+    "!python": 9.814020649250645e-06,
+    "!python3": 5.718552866426749e-06,
+    "!sed": 1.7286587365206637e-05,
+    "!touch": 3.1107159810544953e-07,
+    "\") if \"and: and:": 1.4179077495039095e-06,
+    "\");}1": 6.804691208556708e-08,
+    "\", \"and: ": 1.4179077495039095e-06,
+    "\"PASSWORD\":": 1.4798551754531092e-07,
+    "\"dps\":": 1.722317322843732e-07,
+    "\"func_path_generator\":": 3.018318476666738e-07,
+    "%-d:": 1.1635502524554982e-07,
+    "%-m:": 1.1635502524554982e-07,
+    "%:": 8.563206914138779e-08,
+    "%H:%M:": 1.1635502524554982e-07,
+    "%Y:": 1.1635502524554982e-07,
+    "%autoreload": 2.4388013291467246e-06,
+    "%config": 4.7263591650130315e-07,
+    "%d:": 1.1635502524554982e-07,
+    "%load_ext": 2.6213463388133955e-06,
+    "%m:": 1.1635502524554982e-07,
+    "%paste": 2.5404180511945044e-06,
+    "%run": 3.387224068259339e-06,
+    "%s": 1.4516674578254313e-07,
+    "%version": 1.0887505933690733e-06,
+    "', start='PROGRAM', parser='earley')": 7.816670926752321e-07,
+    "(from": 2.1775011867381466e-07,
+    ")": 1.3254355049710459e-07,
+    ")\n            f.write(": 4.900142373184918e-06,
+    ")\n            prefix = orig.split(": 8.563206914138779e-08,
+    ")\n        new_lines.append(": 5.509340351988082e-06,
+    ") (setv quotechar = \") (setv quoting csv.QUOTE-MINIMAL))'))": 6.59848844466105e-08,
+    ") (setv quotechar = \\\") (setv quoting csv.QUOTE-MINIMAL))'))": 1.31969768893221e-07,
+    ") (setv quotechar = \\\") (setv quoting csv.QUOTE-MINIMAL))'; hy.compile(hy.read_string(repr(code)))": 6.59848844466105e-08,
+    ") and not statement.endswith(": 6.627177524855229e-08,
+    ") f.write(": 2.796790515076519e-07,
+    ") or token.endswith(": 5.011235607835734e-07,
+    "):": 6.627177524855229e-08,
+    ")|": 4.371436344696959e-06,
+    "+": 1.0841824090612311e-06,
+    "+, sql) if s.strip() !=  and s.strip() != ": 2.135137350420284e-06,
+    ",\n    ": 1.8872036008732292e-06,
+    ",\n        ": 4.572752492150108e-07,
+    ",\n    tables=tables\n)\nprint(result)": 2.822686723549449e-07,
+    ", ": 7.024197376574667e-08,
+    ", <>).split(": 6.627177524855229e-08,
+    ", set())": 1.3254355049710459e-06,
+    ",wq": 2.1620579159102167e-07,
+    "...": 4.4996334486101926e-07,
+    ".exit": 2.7769134253297287e-06,
+    ".join(errors)}\")": 9.526567691979392e-07,
+    ".join(errors)}\")\\\n": 9.526567691979392e-07,
+    ".join(errors)}\\\")\"; next } { print }": 9.526567691979392e-07,
+    ".join(qs_strings)": 2.697789080914518e-07,
+    ".join(qs_strings) # replaced with direct rebuild|g": 1.8038471369428435e-07,
+    ".join(qs_strings) - replaced with proper logic|g": 1.665847902422626e-07,
+    ".join(qs_strings)|# qs = ": 3.4696950393654695e-07,
+    ".join(qs_strings)|g": 8.605237981153566e-07,
+    ".join(qs_strings)|qs = ": 4.997543707267878e-07,
+    ".mean().reset_index(0)": 6.944195128549898e-08,
+    ".open": 3.302543466552856e-06,
+    ".tables": 6.036636953333476e-07,
+    ".wq": 8.194896939337112e-08,
+    "0": 6.897717687197699e-06,
+    "0i": 5.942498365367262e-08,
+    "0i@auto_attr": 1.1375006199378378e-07,
+    "1": 5.947601500981958e-06,
+    "1,10d": 3.9133525820711235e-08,
+    "1..2": 8.710004746952586e-07,
+    "100": 2.6055569755841077e-07,
+    "100,110d": 4.8235785782174136e-08,
+    "1000": 7.468959544475334e-07,
+    "10000": 2.2090591749517432e-07,
+    "10000,10200d": 5.080836102389009e-07,
+    "100000": 5.593581030153038e-08,
+    "1000000": 2.5422083387570095e-07,
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+    "=======": 1.960451229217624e-07,
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 {
-  "snapshot_utc": "2026-10-20T19:39:53.280360+00:00",
+  "snapshot_utc": "2026-10-21T22:05:46.361970+00:00",
   "counts": {
     "attempts": 34216,
-    "missing_trajectories": 15538,
+    "missing_trajectories": 1413,
     "raw_missing": 1580,
-    "terminal_errors_zero": 249,
-    "unknown_outcomes": 1331
+    "terminal_errors_zero": 1580,
+    "unknown_outcomes": 0
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   "reward_policy": "terminal-errors-zero-v2",
-  "selection": "All previous selected attempt IDs plus the 96 attempts from the completed 12-task rerun. No failed submissions or duplicate race copies are added."
+  "selection": "All previous selected attempt IDs plus the 96 attempts from the completed 12-task rerun. No failed submissions or duplicate race copies are added.",
+  "recovery": {
+    "baseline_revision": "642a47baeec7edc3b0db072554c7170ca0ea87dd",
+    "snapshot_utc": "2026-10-21T22:05:46.361970+00:00",
+    "source": "RWTH CLAIX runs/swelego-recovery-20261015-c25g, 206 stage-6 evidence archives",
+    "filled": {
+      "result": 15360,
+      "trajectory": 14125,
+      "reward": 1331,
+      "reward_origin": 1331,
+      "selection_reward": 1331
+    },
+    "changed_trace_files": 198,
+    "policy": "Fields are filled only where empty; recorded terminal errors score zero (terminal-errors-zero-v2)."
+  }
 }
\ No newline at end of file
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