Correct the scaling claim the case study could not support - #145
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The case study said the 10-year run cost ~46 s per year of data, "dead linear, which confirms I/O bound with no meaningful per-call overhead." Its own two measurements say otherwise: one year takes 29.1 s and ten take 464.4 s, so a line through them has a negative intercept and each year after the first costs about 48 s. Throughput agrees -- 129 MB/s on the single-year read against 81 MB/s across ten. The likely cause is a warm page cache on the 1979 file, which was read repeatedly while the case study was written, so both numbers are now given with ~48 s/year as the one to plan with and the cache named as a suspicion rather than a result. Two other numbers were wrong. The advertised tool count is 33, not 31, in both write-ups. The demo page still carried a 112 KB PNG and a 320,000:1 ratio from an earlier render; the measured artifact is 177,737 bytes, so the ratio is ~210,000:1. Adds what the case study was missing: the five stages the worker runs, pointers to the full tool menu and the architecture doc, and a reproducing section covering scripts/reproduce_conus_case_study.py and what a rerun showed. That rerun landed on the same PBS job as the original, so its byte-identical PNG is a determinism result and not evidence of reproducibility across allocations -- which the new section says outright. Also links the case study from the root README, where it was not mentioned at all.
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The case study claimed the 10-year run scaled linearly at ~46 s per year, "which confirms I/O bound with no meaningful per-call overhead" — but its own measurements (29.1 s for one year, 464.4 s for ten) fit a line with a negative intercept, so every year after the first costs ~48 s and throughput drops from 129 MB/s to 81 MB/s. Both numbers now appear with the page cache named as the suspected cause rather than a linearity law asserted. Also corrects the tool count (33, not 31) in both write-ups and a stale 112 KB / 320,000:1 figure on the demo page against the measured 177,737-byte artifact.
Adds the five worker stages, links to
docs/tools.mdanddocs/architecture.md, a reproducing section forscripts/reproduce_conus_case_study.py, and a link from the root README, which did not mention the case study at all. The rerun documented there shares a PBS job with the original run, so its byte-identical PNG is called a determinism result and not cross-allocation reproducibility.