Future work — out-of-scope of the current Python MVP

This file consolidates items that are intentionally deferred because they depend on something outside nirs4all-io’s perimeter (a host extension, an external library decision, or a Phase 2 deliverable that has its own gate). Nothing here is a blocker for the lib’s current users; it is a forward log so nothing slips through the cracks when the relevant external pieces move.

dag-ml-data bridge follow-ups

Status: Rust Phase 2 complete. The bridge lives in crates/nirs4all-io-dagml (to_dag_ml_data(&AssembledDataset) + emit-dagml) and is validated by the Phase-2 gate in PHASE2_GATE.md. The Python MVP exposes SpectroDataset, AssembledDataset, and DatasetPackage; it intentionally does not expose a dag-ml-data load target.

Former blockers — both resolved by the dag-ml-data owners (2026-05-28):

  1. ✅ AxisKind::Wavenumber added in dag-ml-data-core/src/model.rs (commit 5063fb0).

  2. ✅ Connector-ownership ADR (ADR-0001, Accepted) — nirs4all-io owns the SpectroDataset → CoordinatorDataPlanEnvelope bridge; dag-ml-data ROADMAP Phase 4 descoped.

Remaining non-MVP items are outside this Python package surface: ergonomic Python builders for dag-ml-data, production array-host arenas in dag-ml-data, and any future decision to expose the emit through language bindings.

SpectroDataset extension on the nirs4all side (host-owned)

Three IR fields are carried but not materialized today because the target SpectroDataset has no first-class slot for them. Extending the host’s SpectroDataset is out of scope for nirs4all-io – the lib does not modify nirs4all (see REPLUG.md).

IR field

Today

Could be (host change)

sample_index.observation_id

parsed; stored as the row’s natural index

SpectroDataset.set_observation_ids() for explicit per-row observation tags (independent of the sample-level group)

sample_index.group_id

parsed; can be smuggled in via metadata

SpectroDataset.set_groups() to drive leakage-aware CV without indirection through metadata

role: weights

surfaced as __sample_weight__ metadata column

SpectroDataset.set_sample_weights() + automatic fit(sample_weight=...) plumbing in the pipeline

For all three, the workaround today is to declare a regular metadata column and read it explicitly in the pipeline.

Inference calibration

infer() returns scores in plan.scores, currently ordinal (triage / ranking). Brier/ECE calibration (story 3.6) requires a labelled vendor/domain-split corpus that we do not have yet. The current uncalibrated behaviour is explicit (Critique C5) and documented; nothing to do until a corpus exists.

Deferred polish

  • Stratified percentage split at load time — intentionally rejected (nirs4all-io is a loader, not a splitter; see DATASET_CONFIGURATIONS.md §7). Stratification belongs in the pipeline’s CV layer.

  • More vendor formats beyond what nirs4all-formats ships – driven by that library’s roadmap, not this one.