---
license: cc-by-4.0
task_categories:
- video-classification
tags:
- human-study
- video-evaluation
- embodied-ai
---

# RoboJudge human study — annotation packages

**16 self-contained, offline annotation packages** covering the 800-item RoboJudge test set.

| packages | items each | total |
|---|---|---|
| `human_study_01..16.zip` | **50** | **800** |

Together: **800 items, no duplicates, full coverage.**
All clips belonging to the same `(dataset, task, episode)` scene stay inside one
package, so a scene is never split across two annotators.

## How to use

1. Download one zip and unpack it.
2. Double-click `index.html` — it runs from `file://`, no server needed.
3. Enter your name, score each clip, then click **Save my results** to export a JSON file.
4. Send that JSON back to whoever assigned you the package.

Progress is kept in `localStorage`, so closing the browser does not lose work — **same machine,
same browser**. Opening the package on a different computer or browser starts from zero.
An internet connection is required: the videos stream from the public dataset.

## What is scored

Per clip, 8 inputs:

- **Physical plausibility (PA)**, 1–5, with three sub-axes (0 fails / 1 partial / 2 ok):
  agent integrity · scene & object consistency · interaction realism
- **Instruction alignment (IA)**, 1–5, with three sub-axes (0 / 1 / 2):
  right agent acts · right object · goal completed

No free text is collected.

## Study design notes

These matter if you analyse the results:

- **Annotators watch the full video at native frame rate.** The automatic judges do not —
  they sample frames (the reference protocol is 4 fps). Annotators therefore see motion
  artefacts that frame-sampled judges cannot. Human and judge scores are **not** same-input
  measurements; treat the human scores as a reference standard rather than as an
  equal-footing comparison.
- **No ground-truth reference video is shown**, and the packages do not contain one.
- **No init frame is shown.** The judges receive video + instruction only, so showing an
  init frame would give annotators strictly more than the judge had.
- Packages carry only `item_id`, `video_url` and `instruction` — **no gold labels and no
  model predictions**, so scoring cannot be anchored by them.