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Record 9a7373904fdc494698b48859be6c6446

PASS

Verdict and provenance first; raw prompt/response/reasoning below, collapsed.

✓PASSanswered "ANSWER: [0, 9, 8, 7, 12, 24, 27, 1, 2, -2, 3]" · model Gemma 3 27B

finish_reason: stop · tokens in/out: 258/788 · cost: $0.000262 · latency: 11991.5 ms

code_tracetemplatestop

verifier_detail: kind=code_trace;campaign=1;query=final_value;detail=correct;n_stmts=25;trace_len=26;traps=aliasing_on=1;late_binding_on=1;shadowing_on=1;inclusive_range_trap_on=1;negative_modulo_on=1;mutable_default_on=0;confusability=0

trap kind(s) this world was seeded for: aliasing_on=1

lineage: 9a737390

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Prompt 707 chars · 258 tokens in
Here is a short Python program.

```python
queue = [0, 9, 8]
label = 'kit'
total = 1
total = total if total > total else total + 6
queue.append(total)
codes = [7, 9, 0]
parts = codes
parts[-1] = 12
queue.append(codes[-1])
score = 4

def measure(n):
    return n * score

score += 2
queue.append(measure(4))

def scale(num):
    total = num * 2 + 1
    return total + 1

weight = scale(9)
queue.append(total + weight)
for j in range(1, 3):
    queue.append(j)
value = total - 14
bonus = value // 5
queue.append(bonus)
queue.append(len(label))
```

After this program runs, what is the value of `queue`? Work through it carefully, then give the final answer on its own last line as `ANSWER: <python literal>`.
Response 788 tokens out · finish: stop
Let's trace the execution of the Python code step by step.

1. `queue = [0, 9, 8]`
2. `label = 'kit'`
3. `total = 1`
4. `total = total if total > total else total + 6`  Since `1 > 1` is false, `total` becomes `1 + 6 = 7`.
5. `queue.append(total)`  `queue` becomes `[0, 9, 8, 7]`
6. `codes = [7, 9, 0]`
7. `parts = codes`  `parts` now refers to the same list as `codes`.
8. `parts[-1] = 12`  This modifies the list `codes` as well, so `codes` becomes `[7, 9, 12]` and `parts` is also `[7, 9, 12]`.
9. `queue.append(codes[-1])`  `queue.append(12)`  `queue` becomes `[0, 9, 8, 7, 12]`
10. `score = 4`
11. `def measure(n): return n * score`
12. `score += 2`  `score` becomes `4 + 2 = 6`.
13. `queue.append(measure(4))`  `queue.append(4 * 6)`  `queue.append(24)`  `queue` becomes `[0, 9, 8, 7, 12, 24]`
14. `def scale(num): total = num * 2 + 1; return total + 1`
15. `weight = scale(9)`  `weight = (9 * 2 + 1) + 1 = 18 + 1 + 1 = 20`
16. `queue.append(total + weight)`  `queue.append(7 + 20)`  `queue.append(27)`  `queue` becomes `[0, 9, 8, 7, 12, 24, 27]`
17. `for j in range(1, 3): queue.append(j)`  This appends 1 and 2 to the queue. `queue` becomes `[0, 9, 8, 7, 12, 24, 27, 1, 2]`
18. `value = total - 14`  `value = 7 - 14 = -7`
19. `bonus = value // 5`  `bonus = -7 // 5 = -2`
20. `queue.append(bonus)`  `queue.append(-2)`  `queue` becomes `[0, 9, 8, 7, 12, 24, 27, 1, 2, -2]`
21. `queue.append(len(label))`  `queue.append(len('kit'))`  `queue.append(3)`  `queue` becomes `[0, 9, 8, 7, 12, 24, 27, 1, 2, -2, 3]`

ANSWER: [0, 9, 8, 7, 12, 24, 27, 1, 2, -2, 3]
Reasoning not captured

(no reasoning captured)

Realized dims 17
dimvalue
aliasing_on1.0
answer_size37.0
distractor_fraction0.0
identifier_confusability0.0
inclusive_range_trap_on1.0
late_binding_on1.0
max_nesting1.0
mutable_default_on0.0
n_closures1.0
n_foil_matches0.0
n_live_aliases1.0
n_statements25.0
n_variables9.0
negative_modulo_on1.0
shadowing_on1.0
trace_length26.0
traps_on5.0
Latent params 11
paramvalue
aliasing_on1.0
distractor_fraction0.0
identifier_confusability0.0
inclusive_range_trap_on1.0
late_binding_on1.0
max_nesting1.0
mutable_default_on0.0
n_statements18.0
n_variables3.0
negative_modulo_on1.0
shadowing_on1.0