README: remove TODO.md references (file deleted)

README.md

@@ -27,7 +27,7 @@ pretty_name: CM-EVS — Coverage-Curated Panoramic RGB-D Dataset
 
 CM-EVS is a curated panoramic RGB-D dataset built under a single principle: **maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible**. The release is structured as one redistributable Blender indoor data archive plus four license-aware adapter packages that regenerate matched frames locally from upstream sources whose terms forbid redistribution.
 
-> **v1.0 status**: this version stages the **full Blender indoor data drop** (374 scene instances, 13,631 ERP RGB-depth-pose frames; 201 from the round1+2 sampling and 173 from round2). The paper's headline `326 scenes / 11,583 frames` is the curator-selected subset that will be derived from this drop after the §5 evaluation experiments finalize. See `TODO.md` for items still in flight.
+> **v1.0 status**: this version stages the **full Blender indoor data drop** (374 scene instances, 13,631 ERP RGB-depth-pose frames; 201 from the round1+2 sampling and 173 from round2). The paper's headline `326 scenes / 11,583 frames` is the curator-selected subset that will be derived from this drop after the §5 evaluation experiments finalize.
 
 ## Dataset summary
 
@@ -57,7 +57,7 @@ Every released ERP frame follows a single coordinate convention:
 | `panorama_{NNNN}_depth.npy` | float32 array | ERP range depth (m); NaN or 0 if invalid; absent for some frames where depth was not produced |
 | `pose_{NNNN}.json` | JSON | `q_wc`, position, `camera_type` |
 
-Per-scene `meta.json`, `metadata/selected_viewpoints.json`, `metadata/candidates.jsonl`, `metadata/per_step_log.jsonl` (curator-only) will land here once the curator runs on the merged 374-scene set; see `TODO.md`.
+Per-scene `meta.json`, `metadata/selected_viewpoints.json`, `metadata/candidates.jsonl`, `metadata/per_step_log.jsonl` (curator-only) will land here once the curator runs on the merged 374-scene set.
 
 ## Directory layout
 
@@ -68,7 +68,6 @@ cmevs_hf_release/
 ├── CHANGELOG.md
 ├── croissant.json       (MLCommons Croissant v1.0; passes mlcroissant 1.1 validator)
 ├── SHA256SUMS           (top-level checksums, excluding blender_indoor/scenes/)
-├── TODO.md              (pre-push checklist)
 ├── blender_indoor/
 │   ├── README.md
 │   ├── scenes/sence_indoor_{0001..0374}/{panorama,pose}_{NNNN}.{png,npy,json}
@@ -104,7 +103,7 @@ Following Gebru et al. 2021. (Source: `main.tex` Appendix A — content here is
 
 **Fields.** RGB PNG (2048×1024 for Blender indoor; native source resolution otherwise), float32 range depth (`.npy`), pose JSON with scalar-first `q_wc`, `meta.json`, candidate / viewpoint / per-step-log metadata (curator-produced frames only), source / scene / split ids.
 
-**Missing values.** Invalid depth pixels are NaN or 0 by source convention; per-frame invalid-depth ratio statistics will land in `results/frame_quality.csv` (see TODO).
+**Missing values.** Invalid depth pixels are NaN or 0 by source convention; per-frame invalid-depth ratio statistics will land in `results/frame_quality.csv` .
 
 **Splits.** Default scene-level 70 / 15 / 15 split via `sha256(new_scene_id) % 100`. See `blender_indoor/metadata/splits.json`. The downstream panoramic-depth experiment (paper §4.10) uses a separate 94-scene Blender-indoor subset under its own scene-level split (84 / 10 / 10 = 3,400 / 362 / 423 frames).