Individual skill
nature-machine-intelligence
Use when targeting Nature Machine Intelligence (Nat Mach Intell) or deciding whether an AI, ML, or robotics manuscript fits this venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.
English-NaturalScience-Journal-Skills/skills/nature-machine-intelligence/SKILL.md
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# Nature Machine Intelligence (nature-machine-intelligence)
## Journal positioning
Nature Machine Intelligence is a Springer Nature journal publishing research across machine learning, artificial intelligence, robotics, and their intersections with other sciences and society. It occupies the Nature-family tier, so the bar is not a strong ML method alone but a result with conceptual significance or real-world relevance that will interest researchers across AI and the sciences more broadly. The journal explicitly attends to societal impact, ethics, fairness, and the responsible development of AI — these are not boxes to tick but genuine editorial concerns. Papers that demonstrate a compelling application of AI to a scientific or societal problem alongside methodological rigor are a strong fit.
This skill is a **fit / venue-selection / re-framing** tool. It does not replace the journal's current official submission guidelines. Before submitting, re-check the live author instructions on the Springer Nature site and the submission system.
## When to trigger
- The author names Nature Machine Intelligence or Nat Mach Intell as the target venue.
- An ML or AI paper has strong conceptual novelty or a major real-world application and the author is choosing between this venue and specialized venues.
- A paper applying AI to scientific discovery (biology, chemistry, physics, climate) needs framing for an interdisciplinary Nature-family audience.
- The author wants to assess whether societal/ethics dimensions are adequately addressed and what desk-reject risks exist.