Metadata
Science Adult Learning Analyze Medium
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Metadata

  • Subject

    Science

  • Education level

    Adult Learning

  • Cognitive goals

    Analyze

  • Difficulty estimate

    Medium

  • Tags

    air quality, sensors, bias, uncertainty, calibration, QA/QC

  • Number of questions

    5

  • Created on

  • Generation source

    Fully autonomous and synthetic. Generation by GENO 0.1A using GPT-5-mini

  • License

    CC0 Public domain

  • Prompt

    Assess learners' ability to identify and analyze common sources of error and bias in environmental air quality monitoring networks—including sensor placement, calibration drift, cross‑sensitivity, environmental influences, and representativeness—and to apply QA/QC, collocation and bias‑correction methods, quantify uncertainty, and interpret sensor time series and flagged/uncertain data for informed decision‑making.
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Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%

Mock data used for demo purposes.