Previous pipeline held three overlapping large structures in RAM:
1. `merged: HashMap<Key, HashMap<String, f32>>` — 92k outer × ~60 String
keys inner = ~200 MB of fragmented heap
2. `per_band: HashMap<u32, Vec<ScorePoint>>` — all 23 bands × 92k
ScorePoints before the first write
3. A `scores.clone()` per band during the write loop (doubled that
band's footprint transiently)
Consolidate into:
- Consume `merged` into a compact `Vec<(lat, lon, Conditions,
BandInvariants)>`; the huge String-keyed HashMaps drop as soon as
collection finishes.
- Loop over bands: score → write → vector drops at end of iteration.
One band's ~1.8 MB score vector lives at a time.
Peak heap goes from ~1.5 Gi to ~250 Mi on the chain step. 2 Gi limit
stays, but we now have 8× headroom instead of tight-fit.