> ## Documentation Index
> Fetch the complete documentation index at: https://docs.k16solutions.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Review submission results

> Interpret classification, overall confidence, and sentence-level detection for one submission.

Open a submission from a course report to review the result alongside the submitted text.

<Note>
  AI Detection reports are embedded workbooks. Their tabs, filters, and summary metrics can vary by
  workspace and report version. Follow the labels and metric descriptions in your report; the
  examples below may not all appear.
</Note>

## Understand the result

<AccordionGroup>
  <Accordion title="AI classification">
    The report summarizes the processed submission as **AI Only**, **Mixed**, or **Human Only**.
    This label is a model output, not a finding of misconduct.
  </Accordion>

  <Accordion title="AI confidence or probability">
    The overall percentage expresses the detector's assessment of the submission as a whole. It is
    not the percentage of words written by AI and should not become an automatic decision threshold.
  </Accordion>

  <Accordion title="Sentence detection">
    Highlighting identifies sentences that the detector marked for closer review. Each sentence is
    evaluated separately from the overall submission result.
  </Accordion>
</AccordionGroup>

## Review the submission

<Steps>
  <Step title="Verify the record">
    Confirm the student, course, assignment, submission type, and submission date.
  </Step>

  <Step title="Read the complete work">
    Read the submission before you focus on highlighting. Note quotations, prompts, templates,
    citations, and other structured text.
  </Step>

  <Step title="Compare the signals">
    Consider the classification, overall score, and highlighted sentences together. Expect them to
    reflect different levels of analysis.
  </Step>

  <Step title="Add assignment context">
    Check permitted tools, disclosure requirements, drafts, prior writing, and relevant instructor
    observations.
  </Step>

  <Step title="Follow institutional policy">
    Use the required human review, documentation, communication, and appeal process.
  </Step>
</Steps>

## Explain apparent mismatches

The overall score and sentence highlighting do not need to move together:

* A low overall result can have no highlighted sentences.
* Many highlighted sentences can appear even when the overall result is below 100%.
* A **Mixed** classification can contain both highlighted and unhighlighted text.

These patterns occur because the system evaluates both the complete submission and individual sentences.

<Warning>
  Do not copy a score into a student record as a factual measure of authorship. Preserve the
  context, source report, and human review required by your policy.
</Warning>

See [Interpret results and FAQ](/ai-detection/interpret-results-and-faq) for common questions.