gpt-5.6-sol
nano-gpt-data-curation — graded by the task's verifier against a measured baseline.
- backend
- modal
- variant
- codex azure_ai/gpt-5.6-sol
- metric
- held-out multi-domain perplexity
- actions
- 259
- duration
- 1h 6m
- recorded
- 2026-08-03
run iddclm-nano-curation__d9qdiJV
Everything gpt-5.6-sol did on this task, in order.
download JSON ↗encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python -u submission/curate.py\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":5000,\"tty\":true}); text(JSON.stringify(r))\n"
}exec result
Script completed
Wall time 1.2 seconds
Output:
{"chunk_id":"360ba7","wall_time_seconds":1.000908863,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 20
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "20",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 15.5 seconds
Output:
{"chunk_id":"2898b0","wall_time_seconds":30.001670732,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 21
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "21",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 16.2 seconds
Output:
{"chunk_id":"750592","wall_time_seconds":30.001949861,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,rss,cmd -C python; cat .timer/remaining_secs\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":2000}); text(r.output)\n"
}exec result
Script completed
Wall time 0.1 seconds
Output:
PID ELAPSED %CPU RSS CMD
973 01:09 96.1 4646508 python -u submission/curate.py
4999
The first scoring pass exposed a performance issue in the reproducible script (the initial unigram implementation repeatedly computed logarithms over too much text). I’ve replaced it with precomputed lookup tables and a bounded 256-word probe; this preserves the criterion while making reruns practical. The candidate generation is now in its exact-token pass.
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 23
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "23",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 9.3 seconds
Output:
{"chunk_id":"7e4c23","wall_time_seconds":30.000299331,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 24
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "24",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 16.5 seconds
Output:
{"chunk_id":"8aa798","wall_time_seconds":30.002000426,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,rss,cmd -C python; ls -lh submission/selection.json 2>/dev/null || true\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":1000}); text(r.output)\n"
}exec result
Script completed
Wall time 0.1 seconds
Output:
PID ELAPSED %CPU RSS CMD
973 02:19 94.6 4650604 python -u submission/curate.py
encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 26
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "26",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 14.8 seconds
Output:
{"chunk_id":"82bb37","wall_time_seconds":30.00242552,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 27
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "27",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 9.8 seconds
Output:
{"chunk_id":"c8b8b1","wall_time_seconds":30.001853558,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 28
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "28",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 13.7 seconds
Output:
{"chunk_id":"f1ba34","wall_time_seconds":30.000474644,"session_id":18645,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:18645,chars:\"\\u0003\",yield_time_ms:1000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script completed
Wall time 0.4 seconds
Output:
{"chunk_id":"133827","wall_time_seconds":0.245721311,"exit_code":1,"original_token_count":93,"output":"Traceback (most recent call last):\r\n File \"/workspace/submission/curate.py\", line 177, in <module>\r\n main()\r\n File \"/workspace/submission/curate.py\", line 120, in main\r\n z = doc_score(row['text'], models, totals, broad, broad_total, vocab,\r\n File \"/workspace/submission/curate.py\", line 91, in doc_score\r\n len(TECH.findall(text[:12000]))]\r\nKeyboardInterrupt\r\n"}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const patch = \"*** Begin Patch\\n*** Update File: /workspace/submission/curate.py\\n@@\\n WORD_RE = re.compile(r\\\"[A-Za-z]+(?:'[A-Za-z]+)?|\\\\d+(?:[.,:]\\\\d+)*\\\")\\n+NON_PROSE_RE = re.compile(r\\\"[^A-Za-z\\\\s]\\\")\\n+UPPER_RE = re.compile(r\\\"[A-Z]\\\")\\n@@\\n- alpha = sum(ch.isalpha() or ch.isspace() for ch in text) / nchar\\n+ char_probe = text[:8000]\\n+ alpha = (len(char_probe) - len(NON_PROSE_RE.findall(char_probe))) / len(char_probe)\\n if alpha < .72:\\n return None\\n- ws = words(text)\\n- n = len(ws)\\n+ word_probe = text[:20000]\\n+ ws = words(word_probe)\\n+ n = int(len(ws) * nchar / max(1, len(word_probe)))\\n@@\\n- upper = sum(ch.isupper() for ch in text) / max(1, sum(ch.isalpha() for ch in text))\\n+ upper = len(UPPER_RE.findall(char_probe)) / max(1, alpha*len(char_probe))\\n@@\\n- hints = [len(ENC.findall(text[:12000])), 0, len(NEWS.findall(text[:12000])),\\n- len(TECH.findall(text[:12000]))]\\n+ # Cheap literal marker counts; the unigram distributions do the actual\\n+ # register classification.\\n+ hp = lo[:12000]\\n+ hints = [sum(hp.count(x) for x in (' references',' external links',' was born',' century',' species')),\\n+ 0,\\n+ sum(hp.count(x) for x in ('reuters','according to',' reported',' spokesman',' said ')),\\n+ sum(hp.count(x) for x in ('<code>','<pre>',' python ',' javascript ',' sql ',' linux ',' error ',' function '))]\\n*** End Patch\"; text(await tools.apply_patch(patch))\n"
}exec result
Script completed
Wall time 0.0 seconds
Output:
{}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.exec_command({cmd:\"python -u submission/curate.py\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":5000,\"tty\":true}); text(JSON.stringify(r))\n"
}exec result
Script completed
Wall time 1.2 seconds
Output:
{"chunk_id":"a410af","wall_time_seconds":1.001957016,"session_id":22658,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:22658,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 32
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "32",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 14.7 seconds
Output:
{"chunk_id":"83bfb8","wall_time_seconds":30.001758012,"session_id":22658,"original_token_count":0,"output":""}encrypted chain-of-thought — recorded, not exposed
args
{
"input": "const r = await tools.write_stdin({session_id:22658,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}exec result
Script running with cell ID 33
Wall time 11.0 seconds
Output:
encrypted chain-of-thought — recorded, not exposed
args
{
"cell_id": "33",
"yield_time_ms": 30000,
"max_tokens": 5000
}wait result
Script completed
Wall time 16.4 seconds
Output:
{"chunk_id":"55319f","wall_time_seconds":30.000800655,"session_id":22658,"original_token_count":0,"output":""}