Plagiarism Detection Guide

Text matching (NOT idea matching):
  - Tools compare your text against databases of published content
  - They flag verbatim matches and close paraphrases
  - They do NOT detect idea plagiarism or conceptual theft
  - They do NOT understand context (quoted text may be flagged)

Common databases searched:
  - Published journal articles (via Crossref, Scopus partnerships)
  - Web pages and online content
  - Previously submitted student papers (Turnitin only)
  - Books and dissertations (varies by tool)
  - Preprint servers (arXiv, SSRN)

def interpret_similarity_score(total_score: float,
                                source_breakdown: list[dict]) -> dict:
    """
    Interpret a plagiarism detection similarity report.

    Args:
        total_score: Overall similarity percentage
        source_breakdown: List of dicts with 'source', 'percentage', 'type'
    """
    interpretation = {
        "total_similarity": total_score,
        "risk_level": (
            "low" if total_score < 15
            else "moderate" if total_score < 30
            else "high"
        ),
        "guidance": {
            "low": (
                "Under 15% is typical for original research papers. "
                "Review flagged sections to confirm they are properly quoted "
                "or are common phrases."
            ),
            "moderate": (
                "15-30% warrants review. Check if matches are from your own "
                "prior work (self-citation), methods sections using standard "
                "language, or properly attributed quotations."
            ),
            "high": (
                "Over 30% requires careful review. Large blocks of matched "
                "text must be rewritten, quoted, or properly attributed. "
                "Note: review articles and meta-analyses may legitimately "
                "have higher similarity scores."
            )
        }
    }

    # Categorize sources
    for src in source_breakdown:
        src["action"] = (
            "Verify proper citation" if src["type"] == "journal_article"
            else "Check if self-plagiarism" if src["type"] == "own_prior_work"
            else "Rewrite or quote with attribution"
        )

    interpretation["sources"] = source_breakdown
    return interpretation

Typically acceptable:
  - Reference list entries
  - Standard methodology descriptions ("Informed consent was obtained...")
  - Widely used definitions or established terminology
  - Properly quoted and attributed passages
  - Author name and affiliation blocks
  - Common phrases ("on the other hand", "in this study")

Potentially problematic:
  - Paragraphs copied from other papers without quotation or citation
  - Closely paraphrased passages without citation
  - Reuse of your own prior text without disclosure (self-plagiarism)
  - Translated text from another language without attribution
  - Figures, tables, or data descriptions from other sources

Self-plagiarism occurs when you reuse substantial portions of your
own previously published text without disclosure. This is an issue
because publishers hold copyright on your published work.

Problematic:
  - Copying methods paragraphs from your prior paper verbatim
  - Reusing introduction or discussion text across papers
  - "Salami slicing" -- publishing the same data in multiple papers

Acceptable:
  - Building on your own prior findings (with proper citation)
  - Reusing brief, standard methodological phrases
  - Reproducing your own figures with permission and citation
  - Theses/dissertations reused in subsequent journal articles
    (check journal policy -- most allow this)

Step 1: Read the source passage carefully
Step 2: Close the source -- do not look at it
Step 3: Write the idea in your own words from memory
Step 4: Compare with the original for accuracy
Step 5: Add the citation

Test: If you can cover the original and still write the passage,
you have genuinely paraphrased. If you need to keep looking back
and changing individual words, you are patch-writing (still plagiarism).