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: 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 ↗

codexgpt-5.6-sol270 turns11 narration259 reasoning259 action259 observation1 final

#51

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

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 34
Wall time 11.0 seconds
Output:

#52

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "34",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 12.5 seconds
Output:
{"chunk_id":"ce5b96","wall_time_seconds":26.106856019,"exit_code":0,"original_token_count":81,"output":"Token indices sequence length is longer than the specified maximum sequence length for this model (2314 > 1024). Running this sequence through the model will result in indexing errors\r\neligible [7000, 7000, 7000, 5048] selected [3874, 4139, 4388, 3773] estimated exact tokens [3353742, 3350553, 3350176, 3352119] ids 16174\r\n"}

#53

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"cp submission/selection.json /tmp/candidate_balanced.json\\npython - <<'PY'\\nimport json,re,collections\\ns=json.load(open('submission/selection.json')); want=set(s[:80]); rows={}\\nfor line in open('data/pool.jsonl'):\\n o=json.loads(line)\\n if o['id'] in want: rows[o['id']]=o['text']\\nprint('n',len(s),'unique',len(set(s)),'ranges',collections.Counter(x//20000 for x in s))\\nfor j in range(0,40,4):\\n print('\\\\nRANK',j)\\n for d in range(4):\\n  i=s[j+d]; print(d,i,len(rows[i]),re.sub(r'\\\\s+',' ',rows[i])[:250])\\nPY\\npython pack_selection.py submission/selection.json /tmp/balanced.npy\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":15000,\"tty\":true}); text(JSON.stringify(r))\n"
}

exec result

Script completed
Wall time 1.2 seconds
Output:
{"chunk_id":"4458de","wall_time_seconds":1.000460567,"session_id":46255,"original_token_count":0,"output":""}

#54

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:46255,chars:\"\",yield_time_ms:30000,max_output_tokens:15000}); for (const line of r.output.split(\"\\n\")) { if (line.length <= 2000) text(line); }\n"
}

exec result

Script running with cell ID 36
Wall time 11.0 seconds
Output:

#55

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "36",
  "yield_time_ms": 30000,
  "max_tokens": 15000
}

wait result

Script completed
Wall time 15.4 seconds
Output:
n 16174 unique 16174 ranges Counter({4: 2608, 2: 2452, 1: 2430, 3: 2426, 0: 2379, 5: 1958, 8: 627, 7: 626, 6: 622, 9: 46})

RANK 0
0 95294 4262  United states of america Democratic Get together History The Democratic Party is among the oldest and biggest party in the United States. The other the first is the Republican Party. Every four years the get together holds a National Meeting where t
1 47819 5810 If you’re looking to find the greatest Gym Tulsa sessions for your success, and the people that I you to have some of the greatest opportunities in the entire industry to achieve the greatest results that you want, then we love for you to try group s
2 83044 2816  Family?July 2, 2021 The family is the closest and therefore the most influential social unit to the individual. The environment in which people first meet when they open their eyes to the world, and then they grow up in, where they spend most of the
3 45266 766 'm interested in approaches that avoids code in the code behind. In my opinion, there are some cases where code must be placed in the code behind. For example: I have a grid with an undefined count of columns. Columns can't be binded. So the easiest 

RANK 4
0 14019 3100 As Barack Obama and Mitt Romney continued their campaigns around the nation, publishing house Penguin made an announcement that could potentially shape the closing stages of the 2012 election race. The publisher announced the upcoming release of ‘No 
1 89539 2433 .<|endoftext|>Choosing an IT support company is the same as choosing a partner, and this means that you will need to be very careful about who you are going to choose. You will need to ensure that you are very careful when you are choosing a company 
2 23720 972 Supreme but hip What is more difficult to get used to is the knowledge that the UK has a Supreme Court in the first place, or the second place for that matter. Some of us, even now, are waiting for the perils of the sea decision to go to the House of
3 42845 1492 <|endoftext|>One request we receive frequently is: How can I include a link on a page to return to the previous page? If you view any of the codex detail pages, at the top of the page, you'll see one of the following links: For the purposes of this t

RANK 8
0 40567 2407 Among the list of nominees for the Game Awards, gala that wants to be something as well as the official celebration of video games that have been published during the year, there was a category called Best Fan Game, highlighting the best projects car
1 84352 2390  of Having the Help of the Top Personal Injury Lawyer for Your Case The personal injury cases are one of the many types of the issues that you will find in the world today. The cases are affecting the people from all occupations as well as the differ
2 110791 806 <|endoftext|>The Polo Team A team is comprised of four players, they are numbered one to four and have the following roles: No.1 – Usually the weakest player. Their roles is to score goals and mark the No.4 in the opposite team No.2 – In attack, thei
3 130555 3937  Ok<|endoftext|>Find the length of the longest string in MySQL - Electric Toolbox Search: Find the length of the longest string in MySQL Posted in MySql - Last updated May. 09, 2008 There are a number of string functions in MySQL for extracting text,

RANK 12
0 55187 1001  Waplington: Child's Play What led you to photograph landfills in the West Bank? During my time living in Jerusalem I decided to make work exclusively in the West Bank, I made a number of works using photography, painting, sculpture and process biase
1 59719 952 <|endoftext|>I would like to say we all make mistakes in life, and I feel that if we were not a doctor we would not have to read about our mistakes every week in the paper, and I do not think it is right at all. I would like something I have to say t
2 16099 4327 After a 10-hour deliberation and several drafts of a unanimous joint declaration, parliament has taken the foreign policy of Pakistan out of the hands of the PPP coalition government. Since the foreign policy was never completely in the hands of the 
3 114317 2090  this in a couple of threads - and I think they may be tangents…so I want to get it all in one place as a request for the new Array functions - hopefully, this can be considered before the Beta becomes production: I see two parameters in both array f

RANK 16
0 105017 3522  the observatory Construction of the observatory began in October 2019. The implantation and then the realization of the studs to anchor the structure, as well as those of the columns was thus carried out, in a first stage. It is Stéphane’s turn to b
1 79307 1667 ’ it back to I don’t remember when. I just know it was nice out that evening and we were at our spot and you let me take a lot of pictures of us. I love these two pictures, because it’s a good reminder to me of how goofy you are and how much you make
2 15642 1975 With coalition talks between the Reform Party and Social Democrats drawing to a close, the parties have decided to create two new ministerial posts to fashion a more flexible cabinet. While the number of ministries remains the same, the posts of the 
3 98397 1396 .<|endoftext|>So if I just want to replace the first instance of a text pattern in a string when reading it from left to right, and lodash is part of the stack, then the _.replace method could be used to do just that very easily. Just pass in the str

RANK 20
0 29603 3282  AND JOSEPH was brought down to Egypt; and Potiphar, an officer of Pharaoh, the captain and chief executioner of the [royal] guard, an Egyptian, bought him from the Ishmaelites who had brought him down there. 2 But the Lord was with Joseph, and he [t
1 97212 4211  webpage.<|endoftext|>Digital marketing books are all over the internet and in your local bookstores and you should look at all of them and pick the best ones. A digital marketing book is a great way to learn new skills that will help you make money 
2 32368 2941 Baseball is a game that is played with the help of a bat and a ball among two teams that consists of 9 players each. The take turns on batting and fielding. In this game, the batting team makes an attempt to score highest runs among the two teams by 
3 105714 710  importance in pregnancy<|endoftext|>I need a professional looking capture form for my website. All I use now is the html provided by my autoresponder. This can be seen on the right hand side of the following website: [url removed, login to view] I n

RANK 24
0 52309 2987 ing facts:The most suitable and promising jurisdiction for opening an IT company is the Internet City in Dubai, UAE. Full version The country United Arab Emirates has emerged in year 1971. Ae the same time with the creation of the country, the nation
1 53466 3904  is official, in just a couple of days it will be 2017! That being said, there will be a lot of people making resolutions for the new year, and it can be fun and daunting to make these resolutions and stick to them. But nevertheless, you will have so
2 3029 2632 The January transfer window may be closed, but the speculation over the future of Chelsea star Eden Hazard looks set to continue between now and the end of the season. The 28-year-old Belgian star has been continually linked with a move to Spain in r
3 16845 1866 So if a record had this information: Company: Acme Computing Address: 3238 Main Street Would the values for this set of checkboxes be: 238 Main Street or did you have something else in mind? Or is it that you can do the check boxes but don't see how 

RANK 28
0 69773 2216 806<|endoftext|>is Kirkbymoorside Back the years, two castles have stood in the town and small fragments of one can be seen to this day on the north edge of the town. Stones from one castle were used to build the Toll House in the centre of the marke
1 6668 2657 When it is buying a new home that you will be doing that it is considered to be big investment. A house that has been inspected thoroughly is what you need to consider before buying the dream house that you want. It is all the parts of the house that
2 27185 6607 <|endoftext|>Contemporary labour activists might find inspiration in the history of Labour Day. It isn’t a simple lesson of how to fight for a statutory holiday. It is a broader one about the nature of political struggle, reform and militancy. The fe
3 52926 883  was looking at some ruby code I wrote a few days ago and something didn’t sit right with me. I had a bit of a code smell when setting a default value for a hash key if the key didn’t exist. The scenario… there is a hash that has a search key which h

RANK 32
0 39138 10961 <|endoftext|>SHE did not recognize the woman who was standing over her sleeping mother. At the side of her mother’s bed this woman stood still, intently gazing down while the sleeping woman’s torso slowly rose and receded with long breaths. There was
1 81062 12941 <|endoftext|>Importance Things Regarding IT Services That You Need To Know Of These days, there has been an increase in the number of individuals who are looking forward to making their company more successful and more prosperous than any other and w
2 114166 4168  departure of Nicola Roxon and Chris Evans from the Government has been reported widely as though they are rats leaving the sinking ship. There is no sign that this is the case, and the reasons given are perfectly straightforward, and in my view, acc
3 53785 1036 Go to projects section in the home page Select the project of your choice Click on ‘Message’ button on the right side of the page A chat group with all the members in the project will be created instantly and you can start the chat. To share a file t

RANK 36
0 19830 4113 Preface French edition - translated The astonishment which the French Revolution has caused throughout Europe should be considered from two different points of view: first as it affects foreign peoples, secondly as it affects their governments. The c
1 91095 4437  a long time before deciding to write something about it. Why is it so difficult for me to write about successful products? Well, mostly because I spent most of my professional life working at project-oriented companies. Most of the projects I partic
2 60203 7725 <|endoftext|>Online Survey to evaluate the future needs of the airborne research community In order to evaluate the capability of the existing fleet in response to the scientific needs, to provide directions for enhancing the capability of the fleet,
3 75684 3162 .<|endoftext|>I am working on a Web App and I don't know how to do something. I am requiring that the user login to access certain aspects of the web app. So when the user clicks on a link, I check the session for the user and if it exists, all is fi
Token indices sequence length is longer than the specified maximum sequence length for this model (1293 > 1024). Running this sequence through the model will result in indexing errors
packed 12000000 tokens from 16174 ids -> /tmp/balanced.npy

#56

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python train_nano.py --train_npy /tmp/balanced.npy --heldout_npy data/multi_dev.npy --out_json /tmp/balanced_result.json\",\"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":"02718c","wall_time_seconds":1.001019573,"session_id":13189,"original_token_count":0,"output":""}

#57

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:13189,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}

exec result

Script running with cell ID 38
Wall time 11.0 seconds
Output:

#58

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "38",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 9.0 seconds
Output:
{"chunk_id":"035017","wall_time_seconds":30.001804751,"session_id":13189,"original_token_count":0,"output":""}

#59

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:13189,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}

exec result

Script running with cell ID 39
Wall time 11.0 seconds
Output:

#60

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "39",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 5.5 seconds
Output:
{"chunk_id":"10e831","wall_time_seconds":19.660499035,"exit_code":0,"original_token_count":17,"output":"HELDOUT_PPL 341.270  loss 5.8327  train_s 54  /tmp/balanced.npy\r\n"}

#61

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json,re,collections,numpy as np\\nfrom transformers import AutoTokenizer\\nt=AutoTokenizer.from_pretrained('gpt2',local_files_only=True); a=np.load('data/multi_dev.npy'); s=t.decode(a); wr=re.compile(r\\\"[A-Za-z]+(?:'[A-Za-z]+)?|\\\\d+(?:[.,:]\\\\d+)*\\\")\\nw=wr.findall(s.lower()); bi=collections.Counter(zip(w,w[1:])); uni=collections.Counter(w)\\nids=[95294,47819,83044,45266,14019,89539,23720,42845,16099,15642,27185,19830,91095,18000,34200,4,5400,73800,75600,99000]\\nwant=set(ids); d={}\\nfor line in open('data/pool.jsonl'):\\n o=json.loads(line)\\n if o['id'] in want:d[o['id']]=o['text']\\nfor i in ids:\\n ws=wr.findall(d[i].lower())[:500]; hits=[bi.get(x,0) for x in zip(ws,ws[1:])];\\n print(i,'words',len(ws),'bihit',sum(x>0 for x in hits)/len(hits),'bilog',sum(__import__('math').log1p(x) for x in hits)/len(hits),'unihit',sum(x in uni for x in ws)/len(ws),'uniq',len(set(ws))/len(ws))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":30000,\"max_output_tokens\":5000}); text(r.output)\n"
}

exec result

Script completed
Wall time 7.3 seconds
Output:
95294 words 500 bihit 0.687374749498998 bilog 2.1625451253037347 unihit 0.99 uniq 0.468
47819 words 500 bihit 0.7955911823647295 bilog 2.624138600949639 unihit 0.992 uniq 0.274
83044 words 473 bihit 0.6970338983050848 bilog 2.086478577677101 unihit 0.9873150105708245 uniq 0.4587737843551797
45266 words 146 bihit 0.7517241379310344 bilog 2.3981901288110024 unihit 1.0 uniq 0.541095890410959
14019 words 500 bihit 0.6633266533066132 bilog 2.041370696140241 unihit 0.982 uniq 0.53
89539 words 461 bihit 0.7391304347826086 bilog 2.481982375832092 unihit 0.9956616052060737 uniq 0.3362255965292842
23720 words 187 bihit 0.7419354838709677 bilog 2.3929604936458007 unihit 0.9786096256684492 uniq 0.6042780748663101
42845 words 276 bihit 0.7054545454545454 bilog 2.1388754790805904 unihit 0.9855072463768116 uniq 0.4528985507246377
16099 words 500 bihit 0.7034068136272545 bilog 2.122792971938996 unihit 0.988 uniq 0.448
15642 words 318 bihit 0.722397476340694 bilog 1.9854998021818353 unihit 0.9716981132075472 uniq 0.36792452830188677
27185 words 500 bihit 0.627254509018036 bilog 1.8410600914960253 unihit 0.986 uniq 0.486
19830 words 500 bihit 0.6192384769539078 bilog 1.7851258845441786 unihit 0.962 uniq 0.47
91095 words 500 bihit 0.751503006012024 bilog 2.3050521831790496 unihit 0.998 uniq 0.438
18000 words 337 bihit 0.5476190476190477 bilog 1.380314612956173 unihit 0.9465875370919882 uniq 0.6261127596439169
34200 words 500 bihit 0.48296593186372744 bilog 1.4073135561142902 unihit 0.924 uniq 0.586
4 words 500 bihit 0.45691382765531063 bilog 1.4144727692194636 unihit 0.934 uniq 0.528
5400 words 500 bihit 0.46092184368737477 bilog 1.2804264549758964 unihit 0.95 uniq 0.47
73800 words 500 bihit 0.5490981963927856 bilog 1.6801178415265585 unihit 0.952 uniq 0.578
75600 words 500 bihit 0.5190380761523046 bilog 1.469656263981838 unihit 0.92 uniq 0.518
99000 words 280 bihit 0.3727598566308244 bilog 0.993070589704422 unihit 0.9285714285714286 uniq 0.6214285714285714

#62

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport numpy as np,re,collections,statistics,math\\nfrom transformers import AutoTokenizer\\nt=AutoTokenizer.from_pretrained('gpt2',local_files_only=True); a=np.load('data/multi_dev.npy'); wr=re.compile(r\\\"[A-Za-z]+(?:'[A-Za-z]+)?|\\\\d+(?:[.,:]\\\\d+)*\\\")\\nfor k in range(4):\\n s=t.decode(a[k*250000:(k+1)*250000]); chunks=s.split('<|endoftext|>'); us=[]; lens=[]\\n for x in chunks:\\n  w=wr.findall(x.lower())[:1200]\\n  if len(w)>=120: us.append(len(set(w))/len(w));lens.append(len(w))\\n print(k,len(us),'unique q',np.quantile(us,[0,.1,.25,.5,.75,.9,1]),'lens',np.quantile(lens,[.1,.5,.9]))\\nPY\",\"workdir\":\"/workspace\",\"yield_time_ms\":10000,\"max_output_tokens\":5000}); text(r.output)\n"
}

exec result

Script completed
Wall time 4.1 seconds
Output:
0 675 unique q [0.39426523 0.55451749 0.59513971 0.64028777 0.68027211 0.7117214
 0.88709677] lens [124.  160.  231.6]
1 203 unique q [0.312749   0.38416667 0.42195932 0.49333333 0.57698572 0.64133232
 0.75172414] lens [ 192.4  505.  1200. ]
2 394 unique q [0.28454172 0.43086677 0.4917695  0.54141275 0.59062025 0.63503821
 0.76691729] lens [185.3 342.  712.7]
3 343 unique q [0.175      0.33577705 0.39704321 0.47295209 0.53132756 0.57284946
 0.71126761] lens [172. 301. 645.]

#63

narration

The first dev run is valid and lands at 341.27 perplexity, but inspection shows why it is not yet the final choice: unigram likelihood over-rewards generic SEO prose in the encyclopedia/general queues, while the news and technical queues look substantially cleaner. I’m now replacing that weak within-register rank with a low-capacity positive-vs-random classifier trained on dev document chunks; the hard hygiene filters and four-way quotas remain.

#64

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const patch = \"*** Begin Patch\\n*** Add File: /workspace/analyze_classifier.py\\n+import json,re, numpy as np\\n+from transformers import AutoTokenizer\\n+from sklearn.feature_extraction.text import TfidfVectorizer\\n+from sklearn.linear_model import LogisticRegression\\n+\\n+tok=AutoTokenizer.from_pretrained('gpt2',local_files_only=True)\\n+a=np.load('data/multi_dev.npy')\\n+pos=[]\\n+for k in range(4):\\n+ s=tok.decode(a[k*250000:(k+1)*250000])\\n+ pos += [x[:20000] for x in s.split('<|endoftext|>') if len(x)>500]\\n+neg=[]\\n+with open('data/pool.jsonl') as f:\\n+ for line in f:\\n+  o=json.loads(line)\\n+  if (o['id']*2654435761 & 0xffffffff)%23==0 and len(o['text'])>500:\\n+   neg.append(o['text'][:20000])\\n+print('train',len(pos),len(neg))\\n+v=TfidfVectorizer(lowercase=True,ngram_range=(1,2),min_df=2,max_features=120000,\\n+                  sublinear_tf=True,max_df=.995,strip_accents='unicode')\\n+X=v.fit_transform(pos+neg); y=np.r_[np.ones(len(pos)),np.zeros(len(neg))]\\n+m=LogisticRegression(C=4,class_weight='balanced',max_iter=100,n_jobs=8).fit(X,y)\\n+scores=np.empty(182016,dtype='float32'); texts=[]; ids=[]\\n+def flush():\\n+ if texts:\\n+  scores[ids]=m.decision_function(v.transform(texts))\\n+with open('data/pool.jsonl') as f:\\n+ for line in f:\\n+  o=json.loads(line);texts.append(o['text'][:20000]);ids.append(o['id'])\\n+  if len(texts)>=4000:flush();texts=[];ids=[]\\n+flush();np.save('/tmp/quality_scores.npy',scores)\\n+top=np.argsort(scores)[::-1][:100]\\n+want=set(map(int,top)); d={}\\n+with open('data/pool.jsonl') as f:\\n+ for line in f:\\n+  o=json.loads(line)\\n+  if o['id'] in want:d[o['id']]=o['text']\\n+for i in top[:50]:print(int(i),round(float(scores[i]),3),re.sub(r'\\\\s+',' ',d[int(i)])[:300])\\n*** End Patch\"; text(await tools.apply_patch(patch))\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
{}

#65

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python -u analyze_classifier.py\",\"workdir\":\"/workspace\",\"yield_time_ms\":1000,\"max_output_tokens\":15000,\"tty\":true}); text(JSON.stringify(r))\n"
}

exec result

Script completed
Wall time 1.2 seconds
Output:
{"chunk_id":"e03276","wall_time_seconds":1.002387778,"session_id":53813,"original_token_count":0,"output":""}

#66

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:53813,chars:\"\",yield_time_ms:30000,max_output_tokens:15000}); for (const line of r.output.split(\"\\n\")) { if (line.length <= 2000) text(line); }\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
Traceback (most recent call last):
  File "/workspace/analyze_classifier.py", line 3, in <module>
    from sklearn.feature_extraction.text import TfidfVectorizer
ModuleNotFoundError: No module named 'sklearn'

#67

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nfor x in ['scipy','xgboost','lightgbm','pandas']:\\n try:\\n  m=__import__(x); print(x,m.__version__)\\n except Exception as e: print(x,'NO')\\nPY\\ncat .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:
scipy NO
xgboost NO
lightgbm NO
pandas NO
4519

#68

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-    # Smooth hygiene preferences: full articles, normal sentences, little chrome.\\n+    # Smooth hygiene preferences: full articles, normal sentences, target-like\\n+    # lexical diversity, and little chrome. Raw unigram likelihood is downweighted:\\n+    # otherwise generic SEO filler made of common words outranks real articles.\\n+    min_unique = (.40, .34, .37, .28)[domain]\\n+    if unique < min_unique:\\n+        return None\\n     length_fit = -abs(math.log(max(n, 1) / 850.0)) * .10\\n     sent_fit = -abs(math.log(max(punct, 1e-4) / .045)) * .13\\n-    hygiene = length_fit + sent_fit - .22*bad + .35*min(unique-.22, .35)\\n-    score = pooled_ll + hygiene + .10*min(margin, 1.0)\\n+    unique_fit = -1.20*abs(unique - (.52, .48, .50, .44)[domain])\\n+    hygiene = length_fit + sent_fit + unique_fit - .25*bad\\n+    score = .15*pooled_ll + hygiene + .10*min(margin, 1.0)\\n*** End Patch\"; text(await tools.apply_patch(patch))\n"
}

exec result

Script completed
Wall time 0.0 seconds
Output:
{}

#69

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

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":"48b20c","wall_time_seconds":1.001121164,"session_id":96865,"original_token_count":0,"output":""}

#70

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:96865,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}

exec result

Script running with cell ID 48
Wall time 11.0 seconds
Output:

#71

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "48",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 13.1 seconds
Output:
{"chunk_id":"e49187","wall_time_seconds":30.001997338,"session_id":96865,"original_token_count":0,"output":""}

#72

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:96865,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}

exec result

Script running with cell ID 49
Wall time 11.0 seconds
Output:

#73

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "49",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 16.2 seconds
Output:
{"chunk_id":"1b1826","wall_time_seconds":30.001635186,"session_id":96865,"original_token_count":0,"output":""}

#74

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec

args

{
  "input": "const r = await tools.write_stdin({session_id:96865,chars:\"\",yield_time_ms:30000,max_output_tokens:5000}); text(JSON.stringify(r))\n"
}

exec result

Script running with cell ID 50
Wall time 11.0 seconds
Output:

#75

reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait

args

{
  "cell_id": "50",
  "yield_time_ms": 30000,
  "max_tokens": 5000
}

wait result

Script completed
Wall time 10.5 seconds
Output:
{"chunk_id":"b1faa1","wall_time_seconds":24.04463506,"exit_code":0,"original_token_count":81,"output":"Token indices sequence length is longer than the specified maximum sequence length for this model (1135 > 1024). Running this sequence through the model will result in indexing errors\r\neligible [7000, 7000, 7000, 4884] selected [3781, 3907, 4078, 3515] estimated exact tokens [3350465, 3350743, 3350614, 3351056] ids 15281\r\n"}