Four census runs on this subject spent whatever query ceiling they were given: 363 s of 300, 1,255 s
of 1,200, 1,874 s of 1,800, at question counts of 2,526 and 406. Cost that tracks the budget rather
than the work is not per-question cost, and tier-zero pruning cutting the count six-fold changed
nothing. A census runs one batch, so no census could answer whether the batch itself scales.
One graph, built once, five batch sizes, every one answered:
25 requests 71.4 s 2.86 s each
50 requests 76.0 s 1.52 s each
100 requests 155.4 s 1.55 s each
200 requests 166.7 s 0.83 s each
400 requests 169.7 s 0.42 s each
Sublinear, and roughly 70 s of it is fixed JVM start and graph load. Four hundred dataflow requests
answer in 170 seconds on the graph production cannot finish 406 on.
So the difference is in the request PARAMETERS. The probe sent callDepth=0 and no parameter sources;
production sends callDepth=3 with parameter sources on every entry point, plus a hook table, a
dispatch list and context evidence. Task 13.2 recorded in September that every reproduction outside
the push path answered in under a minute and the difference was not known. Size is now removed as a
candidate and a four-variant probe is running to isolate the rest.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
