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tiennm99 08a408ca96 docs(plans): drop the completed migration plans

Both plans are done and merged, and their contents now describe a tree that no
longer exists — go-parser/, four datasets, npm entry points, a Rust crate. Git
history keeps them.

The parity evidence stays: docs/data-pipeline.md cites parser-parity-result.md
for the recovered foreign-language scores, so that report and the two JSON
snapshots behind it remain, now marked as an archived record.

2026-08-13 22:54:50 +07:00

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Parser parity result

Archived record. This documents a verification run made on 2026-08-13, against a tree that had a Rust parser, npm-script entry points and four datasets — none of which exist now. It is kept because docs/data-pipeline.md cites it as the evidence that the recovered foreign-language scores are real rather than false regex matches. Do not expect the commands below to run.

Comparison of the databases the unified pipeline ships against a baseline built from the pre-refactor code. Run on 2026-08-13 against the tree as it then stood (npm run build:rust && npm run build:db), gate exit code 0.

Inputs:

plans/reports/parser-parity-baseline.json — built with the two separate crates, before any change
plans/reports/parser-parity-current.json — decompressed from .build/public/db/*.db.gz, i.e. the exact bytes published

Result

Dataset	Rows	Columns	Size
2016	877,461	18 → 22	+1.4%
2017	861,068	18 → 22	+2.2%
2017-old	847,348	18 → 22	+2.2%
2017-old2	679,764	18 → 22	+2.2%

Unchanged, for every dataset:

row count
non-NULL count for all 18 pre-existing columns
every field of a deterministic student sample (SBDs ending 0000)

Approved recoveries

Unifying the subject regexes recovered 1,691 foreign-language scores that the old per-year configs discarded. The 2016 config listed 12 subject patterns and the 2017 configs 14; neither list was complete, so candidates who sat German, Japanese or Russian ended up with no foreign-language score at all.

Dataset	Recovered
2016	182 × `tieng_nga`
2017	93 × `tieng_duc`, 512 × `tieng_nhat`
2017-old	85 × `tieng_duc`, 484 × `tieng_nhat`
2017-old2	22 × `tieng_duc`, 313 × `tieng_nhat`

Confirmed real rather than spurious matches:

Every student in all four datasets holds zero or exactly one foreign language — never two — so nothing is duplicated.
Each affected student had all language columns NULL beforehand. SBD 01003198 went from all-NULL to tieng_duc = 8.
Counts track dataset size across the three 2017 generations (93/85/22 German, 512/484/313 Japanese).
Values are ordinary exam scores in the 0–10 range.

These exact counts are pinned as APPROVED_RECOVERY in parser/scripts/verify-parity.js. Any other newly-populated column, or drift in these numbers, still fails the gate.

Columns that must stay empty

Verified 0 non-NULL:

2016: khtn, khxh, gdcd
2017, 2017-old, 2017-old2: ten_cum_thi, gioi_tinh

Reproducing

npm run build:rust && npm run build:db
node parser/scripts/db-stats.js \
  2016=<db> 2017=<db> 2017-old=<db> 2017-old2=<db> > current.json
node parser/scripts/verify-parity.js \
  plans/reports/parser-parity-baseline.json current.json

The baseline cannot be regenerated — it required the two pre-refactor crates, which no longer exist. It is committed for that reason.

Unresolved questions

None.

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