nnInteractive Agent: General-Purpose AI Agents as 3D Image Annotators
3 judges. Scored by all three judges. Only the day’s top stories get the claim check. How far stories are checked
The paper presents nninteractive-agent, which lets general-purpose AI agents such as Claude Code and Codex perform 3D medical and biological image segmentation from plain-language requests, using the nnInteractive model as tools over the Model Context Protocol and no extra training.
Score
0.67total under rubric v2.0
- Significance0.63
- Reader interest0.76
- Audience breadth0.48
- Practical relevance0.73
- Substantiated0.81
- Technical depth0.73
- New information0.92
- Counts against: Promotional0.08
- Counts against: Overclaim0.23
Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).
| Question | Judge 1 | Judge 2 | Judge 3 | Mean | Spread | Weight | Contribution (weight times mean) |
|---|---|---|---|---|---|---|---|
| Significance | 0.60 | 0.55 | 0.75 | 0.63 | 0.20 | +0.25 | +0.158 |
| Reader interest | 0.72 | 0.60 | 0.95 | 0.76 | 0.35 | +0.20 | +0.151 |
| Audience breadth | 0.43 | 0.45 | 0.55 | 0.48 | 0.12 | +0.10 | +0.048 |
| Practical relevance | 0.76 | 0.60 | 0.82 | 0.73 | 0.22 | +0.15 | +0.109 |
| Substantiated | 0.93 | 0.70 | 0.80 | 0.81 | 0.23 | +0.10 | +0.081 |
| Technical depth | 0.73 | 0.65 | 0.82 | 0.73 | 0.17 | +0.10 | +0.073 |
| New information | 0.94 | 0.85 | 0.97 | 0.92 | 0.12 | +0.10 | +0.092 |
| Promotional | 0.09 | 0.10 | 0.05 | 0.08 | 0.05 | −0.15 | −0.012 |
| Overclaim | 0.26 | 0.25 | 0.18 | 0.23 | 0.08 | −0.15 | −0.035 |
| Sum of contributions | +0.666 | ||||||
| Claim-check penalty | 0.000 | ||||||
| Total, as published | 0.666 | ||||||
Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.
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Elsewhere
Elsewhere: HN —
Recorded for context only, checked 24 Oct 2026, 08:54 UTC. It played no part in the ranking.