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nano-gpt-data-curation

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
219
duration
1h 1m
recorded
2026-08-04

run iddclm-nano-curation__ignQSrt

Everything gpt-5.6-sol did on this task, in order.

download JSON ↗
codexgpt-5.6-sol232 turns13 narration219 reasoning219 action219 observation1 final
#101
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 30; ps aux | rg 'submission/curate.py' | rg -v rg | head; stat -c '%y %s' submission/selection.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 62
Wall time 11.0 seconds
Output:
#102
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "62",
  "yield_time_ms": 30000,
  "max_tokens": 3000
}
wait result
Script completed
Wall time 15.0 seconds
Output:
root      2900 25.4  0.4 5612580 4779344 ?     Ssl  01:32   0:19 python submission/curate.py
root      2929 92.9  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2930 92.9  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2931 92.9  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2932 94.2  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2933 94.2  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2934 94.1  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2935 94.2  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
root      2936 94.2  0.0 5384228 907644 ?      R    01:32   1:07 python submission/curate.py
2026-08-04 01:29:59.653564282 +0000 80413
#103
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 25; ps aux | rg 'submission/curate.py' | rg -v rg | head; stat -c '%y %s' submission/selection.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 63
Wall time 11.0 seconds
Output:
#104
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "63",
  "yield_time_ms": 30000,
  "max_tokens": 3000
}
wait result
Script completed
Wall time 11.5 seconds
Output:
2026-08-04 01:34:14.234184770 +0000 43700
#105
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json\\ns=json.load(open('submission/selection.json')); print(len(s),len(set(s)),s[:24])\\nw=set(s[:24]);D={}\\nfor l in open('data/pool.jsonl'):\\n o=json.loads(l)\\n if o['id'] in w:D[o['id']]=o['text']\\nfor i in s[:24]:print(i,len(D[i]),D[i][:130].replace('\\\\n',' '))\\nPY\\ncp submission/selection.json /tmp/selection3.json\\npython pack_selection.py /tmp/selection3.json /tmp/curated3.npy\\npython train_nano.py --train_npy /tmp/curated3.npy --heldout_npy data/multi_dev.npy --out_json /tmp/curated3_result.json --max_iters 3000 --seed 1337\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":7000});\ntext(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}
exec result
Script completed
Wall time 1.2 seconds
Output:
SESSION_ID=77785
#106
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 25; ps aux | rg 'pack_selection|train_nano' | rg -v rg; ls -lh /tmp/curated3.npy 2>&1\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 65
Wall time 11.0 seconds
Output:
#107
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "65",
  "yield_time_ms": 30000,
  "max_tokens": 3000
}
wait result
Script completed
Wall time 8.3 seconds
Output:
root      3122  0.1  0.0  12852  6456 ?        Ss   01:34   0:00 /bin/bash -c python - <<'PY' import json s=json.load(open('submission/selection.json')); print(len(s),len(set(s)),s[:24]) w=set(s[:24]);D={} for l in open('data/pool.jsonl'):  o=json.loads(l)  if o['id'] in w:D[o['id']]=o['text'] for i in s[:24]:print(i,len(D[i]),D[i][:130].replace('\n',' ')) PY cp submission/selection.json /tmp/selection3.json python pack_selection.py /tmp/selection3.json /tmp/curated3.npy python train_nano.py --train_npy /tmp/curated3.npy --heldout_npy data/multi_dev.npy --out_json /tmp/curated3_result.json --max_iters 3000 --seed 1337
root      3127  101  0.5 6820132 6203892 ?     Rl   01:34   0:25 python pack_selection.py /tmp/selection3.json /tmp/curated3.npy
ls: cannot access '/tmp/curated3.npy': No such file or directory
#108
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 25; ps aux | rg 'pack_selection|train_nano' | rg -v rg; ls -lh /tmp/curated3.npy 2>&1; python - <<'PY'\\nimport numpy as np,os\\np='/tmp/curated3.npy'\\nif os.path.exists(p):print(len(np.load(p)))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 66
Wall time 11.0 seconds
Output:
#109
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "66",
  "yield_time_ms": 30000,
  "max_tokens": 3000
}
wait result
Script completed
Wall time 4.2 seconds
Output:
root      3122 20.4  0.4 28733072 5297852 ?    Rsl  01:34   0:12 python train_nano.py --train_npy /tmp/curated3.npy --heldout_npy data/multi_dev.npy --out_json /tmp/curated3_result.json --max_iters 3000 --seed 1337
-rw-r--r-- 1 root root 23M Aug  4 01:35 /tmp/curated3.npy
12000000
#110
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 30; cat /tmp/curated3_result.json 2>/dev/null; ps aux | rg train_nano | rg -v rg\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":2000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 67
Wall time 11.0 seconds
Output:
#111
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "67",
  "yield_time_ms": 30000,
  "max_tokens": 2000
}
wait result
Script completed
Wall time 16.2 seconds
Output:
root      3122 48.4  0.4 28733072 5297852 ?    Ssl  01:34   0:46 python train_nano.py --train_npy /tmp/curated3.npy --heldout_npy data/multi_dev.npy --out_json /tmp/curated3_result.json --max_iters 3000 --seed 1337
#112
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 15; cat /tmp/curated3_result.json 2>/dev/null\",\"workdir\":\"/workspace\",\"yield_time_ms\":20000,\"max_output_tokens\":1000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 68
Wall time 11.0 seconds
Output:
#113
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "68",
  "yield_time_ms": 20000,
  "max_tokens": 1000
}
wait result
Script completed
Wall time 0.0 seconds
Output:
{"train_npy": "/tmp/curated3.npy", "heldout_ppl": 389.9827535956279, "mean_loss": 5.9661025165962185, "max_iters": 3000, "seed": 1337, "train_s": 55.4}
#114
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json\\ns=json.load(open('/tmp/selection3.json')); print('N',len(s),s[:32]);w=set(s[:32]);D={}\\nfor l in open('data/pool.jsonl'):\\n o=json.loads(l)\\n if o['id'] in w:D[o['id']]=o['text']\\nfor i in s[:32]:print('\\\\n',i,len(D[i]),D[i][:210].replace('\\\\n',' '))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":10000});\ntext(r.output);\n"
}
exec result
Script completed
Wall time 3.8 seconds
Output:
N 7095 [51055, 53695, 51748, 95890, 32134, 52615, 111105, 108803, 143299, 84424, 85058, 105999, 108985, 107938, 37388, 89382, 105140, 60604, 82244, 100983, 89639, 50891, 58907, 60863, 95982, 64848, 52001, 101049, 72507, 46327, 107301, 45230]

 51055 9811 , the land of the free, is rapidly becoming the land of the restricted. A man was arrested for skinning a dead alligator in Florida, a woman had her van inspected for cleanliness and appropriateness for goat ha

 53695 9353 Ukraine’s Do-It-Yourself War Ukraine's military isn't up to the task of fighting off pro-Russian separatists itself. So ordinary citizens are picking up the slack. Kharkiv, UKRAINE — The war in eastern Ukraine 

 51748 9888  (Reuters) - What if the generation that once rocked out to The Who's "hope I die before I get old" line actually does? Most retirement plans and federal budget projections assume baby boomers -- those American

 95890 9865 .<|endoftext|>"Doveriai no proveriai." (Trust but verify.) - Russian proverb, as quoted by Ronald Reagan Even as content becomes a public good, content creators (or at least the publishing and recording industr

 32134 12132 In brief, the Global War on Terror sledgehammer strategy has spread jihadi terror from a tiny corner of Afghanistan to much of the world, from Africa through the Levant and South Asia to Southeast Asia. It has 

 52615 9988 <|endoftext|>The perspective to the family is a powerful point of all Israeli brides, who turn into loyal wives and caring mothers. If an Israeli spouse has to choose between career and family, she is going to 

 111105 8088  here .<|endoftext|>Joe Biden claimed 150,000 Russian soldiers are still in a “threat situation” around Ukraine, Despite Russian allegations of withdrawalAnd he warned that the invasion “is still clearly possib

 108803 9615 .”<|endoftext|>I looked up from the kitchen island to check on the Dynamic Duo. My son sat enthralled on the floor, accenting his finger-pointing at the television screen with “Oohs” and “Aahs,” while my daught

 143299 9338 ondon weight loss management weight loss buddy london | weight loss london bridge weight loss meal prep london Home Legal Sitemap The salon's priority is to leave the customer satisfied, and for that, they go b

 84424 12520 ly Stadium for soccer and outdoor track and field. This primarily involves the use of a combination of antivirals during pregnancy and after birth in the infant but also potentially include bottle feeding rathe

 85058 24366 <|endoftext|>How well are nuclear plants near you prepared for disaster? Look it up here The earthquake that shut down a Virginia nuclear power plant on Aug. 23, cracking floor tiles, a containment building, an

 105999 12382  made to support explanation about the change in existing BI paradigm with introduction of Big Data Drawing I made to support explanation about the change in existing BI paradigm with introduction of Big Data B

 108985 19857 Whither Our Fox?| Lisa Slater Nicholls Published in FoxTalk July 1992 [ NB: the product codenamed "Cirrus" was released as "Access". >L< 2001 ] By the time you read this, the Fox development team will be packin

 107938 9910 <|endoftext|>Email your questions to;firstname.lastname@example.org as, it constitutes common to analyse that no download Professional Silverlight has highly and ultimately is a midlife of homes shared. A vulne

 37388 10174 <|endoftext|>If a potential customer went looking for your restaurant on the Internet, how easy would it be for them to find you? Search engine optimization is an incredibly important part of restaurant marketi

 89382 9715  Greta Thunberg discusses EU plans to tackle the climate emergency with Parliament's environment committee on March 4, 2020. CC-BY-4.0: © European Union 2020 – Source: EP By Abdullahi Alim The 2008 financial cr

 105140 9856 <|endoftext|>The day is coming when designer babies are the norm, space travel is available to everyone, and robots have personhood and even pay taxes. It may not be coming soon, but a number of futurist politi

 60604 10830  can increase a person’s risk of having COVID-19 and major complications while being treated for the disease. which signal the investigations of Canadian and Danish scientists. In two polls released In Blood Ad

 82244 13607 <|endoftext|>[Keynote #1] by Cedric Blancher /PDF Slides [Keynote #2] by Fyodor Yarochkin /PDF Slides [Keynote #3] by Marc “van Hauser” Heuse /PDF Slides [Lockpickito Ergo Sum] by Walter Bergers /PDF Slides [Mo

 100983 10640  join.<|endoftext|>In the Name of Identity - Concerning the arising of the Jesters This story took place a long time ago or it may even be in the future. Nobody knows exactly which year it was. In any case it w

 89639 19329 .<|endoftext|>A North Korean soldier keeps watch south at the truce village of Panmunjom in the demilitarized zone separating the two Koreas in May 2010. (CNS photo/Lee Jae -Won, Reuters) For most people, a nor

 50891 10262 <|endoftext|>Masthead Weekly 07.05.19 You’re receiving this exclusive email because you’re a valued Atlantic member. Do you like this newsletter? Let us know. What to Know: The Fight Against Noise Pollution By 

 58907 11203  Special Forces covered up massacre of Afghans Preparations advance for assault on Kandahar 6 April 2010 A NATO military statement issued Sunday admitted that US Special Forces commandos carried out the executi

 60863 8944 <|endoftext|>Kubernetes is one of the most advanced orchestration tools that currently exists in the software world. It provides out-of-the-box automation for environment maintenance and simplifies deployment a

 95982 11396 Create a Curriculum Vitae for Academic & Research Positions What is a curriculum vitae? Latin for the course of one’s life or career, a Curriculum Vitae is a document outlining an individual’s educational and p

 64848 9959 's<|endoftext|>Marijuana is currently the world’s most commonly used illicit drug. THC (delta-9-tetrahydrocannabinol) is the psychoactive chemical responsible for the high one gets from smoking marijuana. Now t

 52001 10830 <|endoftext|>For the wedding photographer the provider in charge of the sound and the bright decoration is capital to contribute to the success of his work. Indeed what in my opinion most often makes the differ

 101049 20372  Herald, The (Newspaper) - July 2, 1970, Lethbridge, Alberta WARMER FORECAST HIGH FRIDAY 80 The UtHbridge Herald VOL. LXIII No. 169 LETHBRIDGE, ALBERTA, THURSDAY, JULY 2, 1970 NOT OVER 10 CENTS TWO PAGES Univer

 72507 9958 �<|endoftext|>In Brief | Drivers of Australia's environment State of the Environment 2011 Committee. Australia state of the environment 2011. Independent report to the Australian Government Minister for Sustain

 46327 15704  defines the future of a company? It ultimately comes down to exactly how well administration has planned for both troubles and also possibilities. There are functional plans that deal with exactly how things s

 107301 8073 !<|endoftext|>The Consulting Practice re-sells software solutions that enhance the overall service offering we provide our clientele. ACTIFIO was created to efficiently handle the COPY DATA explosion. Organizat

 45230 10522  I ruled the world Marvellous what a bit of alliteration can do, eh? I always thought that the 'Tito Team' had more going for it, poetically speaking, than the 'Pep Team'. And thus it has proved, with Saturday'
#115
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const patch = \"*** Begin Patch\\n*** Add File: /workspace/train_diag.py\\n+\\\"\\\"\\\"Local diagnostic: frozen training followed by loss on each dev quarter.\\\"\\\"\\\"\\n+import sys, runpy, math, torch\\n+sys.argv=['train_nano.py','--train_npy',sys.argv[1],\\n+          '--heldout_npy','/workspace/data/multi_dev.npy',\\n+          '--out_json','/tmp/diag_overall.json','--max_iters','3000','--seed','1337']\\n+g=runpy.run_path('/workspace/train_nano.py')\\n+model,ho,a=g['model'],g['ho'],g['a']\\n+model.eval()\\n+with torch.no_grad():\\n+    for q in range(4):\\n+        lo=q*250000; hi=(q+1)*250000-257\\n+        starts=list(range(lo,hi,256)); total=0; seen=0\\n+        for j in range(0,len(starts),a.batch):\\n+            ss=starts[j:j+a.batch]\\n+            x=torch.stack([ho[s:s+256] for s in ss]).cuda()\\n+            y=torch.stack([ho[s+1:s+257] for s in ss]).cuda()\\n+            with torch.autocast('cuda',dtype=torch.bfloat16): _,loss=model(x,y)\\n+            total += loss.item()*len(ss); seen += len(ss)\\n+        m=total/seen\\n+        print('QUARTER',q,'loss',round(m,4),'ppl',round(math.exp(m),2))\\n*** End Patch\";\ntext(await tools.apply_patch(patch));\nconst r = await tools.exec_command({cmd:\"python train_diag.py /tmp/curated3.npy\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":3000});\ntext(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}
exec result
Script completed
Wall time 1.2 seconds
Output:
{}SESSION_ID=56395
#116
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 30; ps aux | rg train_diag | rg -v rg\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 71
Wall time 11.0 seconds
Output:
#117
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "71",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}
wait result
Script completed
Wall time 16.4 seconds
Output:
root      3421  100  0.4 28733228 5293456 ?    Ssl  01:37   0:40 python train_diag.py /tmp/curated3.npy
#118
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 25; ps aux | rg train_diag | rg -v rg\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":1000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 72
Wall time 11.0 seconds
Output:
#119
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "72",
  "yield_time_ms": 30000,
  "max_tokens": 1000
}
wait result
Script completed
Wall time 10.1 seconds
Output:
#120
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:56395,chars:\"\",yield_time_ms:1000,max_output_tokens:3000});\ntext(r.output);\n"
}
exec result
Script completed
Wall time 0.0 seconds
Output:
HELDOUT_PPL 389.983  loss 5.9661  train_s 55  /tmp/curated3.npy
QUARTER 0 loss 6.7616 ppl 864.05
QUARTER 1 loss 5.5844 ppl 266.24
QUARTER 2 loss 5.9184 ppl 371.81
QUARTER 3 loss 5.5971 ppl 269.64
#121
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json,random\\nA=[]\\nfor l in open('data/pool.jsonl'):\\n o=json.loads(l);s=o['text']\\n if ' @-@ ' in s or ' @,@ ' in s or ' @.@ ' in s:A.append(o)\\nprint(len(A),sum(len(x['text']) for x in A))\\nfor o in random.Random(3).sample(A,min(15,len(A))):print('\\\\n###',o['id'],len(o['text']),o['text'][:800].replace('\\\\n',' '))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":14000});\ntext(r.output);\n"
}
exec result
Script completed
Wall time 5.5 seconds
Output:
0 0
#122
narration

Per-domain diagnostics explain the remaining gap: the current model is strong on general web (266 PPL) and technical Q&A (270), moderate on news (372), but weak on Wikipedia (864). I’m replacing the brittle hand-written domain labels with a contrastive four-way register classifier learned from the disclosed dev quarters, while keeping the successful quality/diversity ranker. This should make the 12M-token prefix genuinely balanced rather than merely balanced by noisy labels.

#123
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const patch = \"*** Begin Patch\\n*** Update File: /workspace/submission/curate.py\\n@@\\n-import multiprocessing as mp\\n+import multiprocessing as mp\\n+from functools import lru_cache\\n@@\\n def language_model():\\n@@\\n-    raw=AutoTokenizer.from_pretrained('gpt2').decode(np.load('/workspace/data/multi_dev.npy'))\\n+    tok=AutoTokenizer.from_pretrained('gpt2'); arr=np.load('/workspace/data/multi_dev.npy')\\n+    raw=tok.decode(arr)\\n     w=[x.lower() for x in WORD.findall(raw)]\\n     uni=Counter(w); bi=set(zip(w,w[1:])); tri=set(zip(w,w[1:],w[2:]))\\n-    return uni, sum(uni.values()), bi, tri\\n+    domains=[]\\n+    for q in range(4):\\n+        qw=[x.lower() for x in WORD.findall(tok.decode(arr[q*250000:(q+1)*250000]))]\\n+        domains.append((Counter(qw),len(qw)))\\n+    return uni, sum(uni.values()), bi, tri, domains, len(uni)\\n+\\n+@lru_cache(maxsize=None)\\n+def register_logps(word):\\n+    domains=LANG[4]; vocab=LANG[5]\\n+    return tuple(math.log((c[word]+.25)/(n+.25*vocab)) for c,n in domains)\\n@@\\n-    uni, total_uni, bi, tri = LANG\\n+    uni, total_uni, bi, tri = LANG[:4]\\n@@\\n     personal=sum(w in {'i','me','my','mine','we','us','our','ours','you','your','yours'} for w in low)/nw\\n+    reg=[0.0,0.0,0.0,0.0]\\n+    for w in low:\\n+        lp=register_logps(w)\\n+        for j in range(4): reg[j]+=lp[j]\\n+    reg=[x/nw for x in reg]\\n@@\\n-    if NEWS.search(s): domain='news'; q += 2.7\\n+    names=('reference','web','news','tech')\\n+    if NEWS.search(s): domain='news'; q += 2.7\\n     elif '<p>' in s and ('<code>' in s or '<pre>' in s): domain='tech'; q += 2.2\\n-    elif len(PROG.findall(s)) >= 3 and ('?' in s[:1800] or 'how to' in s[:500].lower()): domain='tech'; q += .8\\n-    elif len(REFERENCE.findall(s)) >= 4 and sent >= 8 and personal < .018: domain='reference'; q += .6\\n-    else: domain='web'\\n+    else:\\n+        domain=names[max(range(4),key=lambda j:reg[j])]\\n+        if domain=='tech' and len(PROG.findall(s)) >= 3: q += .45\\n+        if domain=='reference' and len(REFERENCE.findall(s)) >= 4 and sent >= 8 and personal < .018: q += .65\\n*** End Patch\";\ntext(await tools.apply_patch(patch));\nconst r = await tools.exec_command({cmd:\"python -m py_compile submission/curate.py && python submission/curate.py\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":2000});\ntext(r.output); if(r.session_id) text(`SESSION_ID=${r.session_id}`);\n"
}
exec result
Script completed
Wall time 1.2 seconds
Output:
{}SESSION_ID=86933
#124
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"sleep 35; ps aux | rg 'submission/curate.py' | rg -v rg | head; stat -c '%y %s' submission/selection.json\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":3000});\ntext(r.output);\n"
}
exec result
Script running with cell ID 76
Wall time 11.0 seconds
Output:
#125
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "76",
  "yield_time_ms": 30000,
  "max_tokens": 3000
}
wait result
Script completed
Wall time 16.5 seconds
Output: