BUILD_LOG.md

Build log — 2026-09-09

Rebuild of all tables from the 1,296 source databases, adding trajectories.parquet, impressions.slot, actions.step, and correcting the step column.

Commands

python build_divdata.py       --out divdata/                         # 6 core tables, ~2h15 single process
python build_trajectories.py  --out divdata/ --workers 16 --patch-steps   # trajectories + step back-fill

Source: <run>.db (SQLite, OASIS schema) + <run>.metadata.json (agent → model map)

• <run>_chats.jsonl (one row per activation: step, status, attempts with the model's response and tool call) + <run>_reasoning.jsonl (thinking channel, where exposed). 1,384 databases found; 88 skipped (no metadata sidecar, or an in-progress checkpoint).

Output

table	rows	size	step non-null
runs	1,296	34 KB	—
agents	28,938	24 KB	—
posts	89,171	23.8 MB	90.2%
comments	652,588	91.8 MB	91.8%
impressions	14,020,992	1.2 MB	93.3%
actions	741,219	6.1 MB	91.7%
trajectories	748,285	169.6 MB	89.5% (of feed-fetch activations)

Row counts of the six core tables are identical to the previous release; only step values, and the new columns, changed.

Trajectories build log (_trajectories_build_log.json)

runs 1296        no_chats 41 (no sidecar → timestamps and actions only, no step/decision)
agents 28847     agents_aligned 26786 (92.9%)   agents_multi 339 (see below)
activations 748285 = 741219 actions + 7066 passive (fetched the feed, no action landed)
status: ok 670505 · exhausted 2263 · exception 79 · null 75438 (unaligned agents)
with_tool_call 642083 · with_response_text 258949 · with_reasoning 284788
windows_multi 3247 (extra_in_window rows)

Validation:

• every action in actions.parquet is present in trajectories (741,219 = 741,219);
• every feed-fetch window holds at most one action in all but 16 runs;
• where trajectories.step and the action-count alignment of posts/comments both give a value, they agree on 624,776 / 624,820 rows (99.993%); all 44 disagreements are in 5 of those 16 runs;
• --patch-steps back-filled step from the feed-fetch alignment where the action-count alignment had NULL: posts 15,060 → 8,701 NULL; comments 91,744 → 53,403; actions 106,264 → 61,564. Agreement on rows both methods covered: 99.995 / 99.993 / 99.993%.

The 16 runs with two actions in one feed-fetch window

In decreasing number of extra actions: archive_20260516_1003/oasis_v9_hetero_late (2,468 — an early v9 run whose harness allowed multiple actions per activation), sweep_olmo_mag_s42 (98), sweep_mag_olmo_s42 (97), tetratic/tetra_s271_r4 (82), tetratic/tetra_s271_r3 (81), attractor_rl/eval_runs_triadic/baseline/eval_baseline_s43 (72), …_s42 (66), tetratic/tetra_s42_r5 (57), sweep_glm47_glm47_qwe_s137 (51), sweep_glm47_glm47_qwe_s42 (36), sweep_tri_glm_qwe_gem_s999 (36), sweep_tri_glm_qwe_gem_s271 (32), tetratic/tetra_s42_r6 (31), sweep_tri_gem_mag_glm_s999 (20), sweep_tri_gem_mag_glm_s271 (16), sweep_tri_gem_qwe_glm_s42 (4). For an agent with any such window the refresh alignment is not trustworthy, so its step, status and decision fields are NULL in trajectories (339 agents); its actions are all present, extras flagged extra_in_window=True, and refreshed_at / acted_at are exact. Step coverage in these runs is 0–58%. Prefer created_at ordering there.

Erratum in the previous release (published 2026-09-04)

build_divdata.py assigned step by iterating all of an agent's posts, then all of its comments, while the alignment index assumed one time-ordered stream. Consequence, measured by rebuilding and comparing on the same rows:

table	rows compared	old step == new step
posts	74,111	38.9%
comments	560,844	49.2%
impressions	per viewer	0% of viewers had the same step set — every value shifted by one activation (the step-0 intro post has no feed fetch, and was counted as one)

Agents that only ever commented, and the step-0 intro posts, were correct; everything else was scrambled. No other column was affected. actions.step was NULL throughout in the old release. Nothing in the accompanying paper used step.

Decision-record coverage by model (feed-fetch activations)

model	activations	response_text	reasoning	tool_call	passive
gpt-oss-20b	247,489	0.4%	4.8%	94.4%	0.3%
Magistral-Small-2509	149,666	86.2%	91.7%	91.3%	1.1%
Qwen3-32B	102,546	44.6%	44.7%	90.2%	0.3%
GLM-4-32B-0414	54,430	0.0%	0.0%	95.7%	0.6%
gemma-4-31B-it	39,744	93.0%	93.4%	92.7%	1.2%

tool_call < 100% because unaligned agents carry no decision record. gpt-oss and GLM-4 never emit visible deliberation.

Addendum 2026-09-28 — comments.parquet gains parent_comment_id

The simulator records threaded replies (comment.parent_comment_id) and the first release dropped the column. Back-filled from the source databases; no other column, row count, or order changed.