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Artifacts generated during inference for technical researchers and MLOps engineers. This field may include:
  • reasoning traces, such as chain-of-thought, tree-of-thought, or graph-of-thought prompting paths;
  • context retrieved during retrieval-augmented generation;
  • agent interaction traces, such as iterative hypothesis testing or round-table discussions among AI agents;
  • uncertainty estimates, such as confidence scores, prediction intervals, generation quality metrics, or entropy-based measures; and
  • interpretability artifacts, including attribution maps, feature-importance scores, or saliency maps.
For models that update continuously or episodically, including self-evolving models or agents with Bayesian updating, persistent memory, lifelong learning, or dynamic routing or reconfiguration, this field may also record relevant model states or memory snapshots. These records allow retrospective reconstruction of the model configuration at the time of use with greater detail than using only the version identifier from the Model instance field.