Answer: (iii) deterministic and non-deterministic distortions

Artifacts in a dataset are unwanted distortions or errors introduced into the data during collection, transmission, or measurement (e.g., sensor noise, transmission glitches, encoding errors). They can arise from:

• Deterministic distortions — predictable, systematic effects (e.g., a fixed sensor calibration bias).
• Non-deterministic distortions — random, unpredictable effects (e.g., random noise).

Since artifacts can stem from either or both causes, the correct characterization is (iii) both deterministic and non-deterministic distortions.