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Troubleshooting

Solutions to common issues you might encounter when using qualcode.ai.

File Upload Issues

File format not supported

qualcode.ai supports the following file formats:

  • CSV (.csv) - Comma-separated values
  • Excel (.xlsx, .xls) - Microsoft Excel spreadsheets

If your file isn't uploading:

  • Check the file extension matches one of the supported formats
  • Try exporting from your spreadsheet software as CSV
  • Ensure the file isn't corrupted by opening it locally first

Encoding errors or garbled text

If your data contains special characters, accents, or non-English text that appears garbled:

  • Save your CSV with UTF-8 encoding
  • In Excel: File > Save As > choose "CSV UTF-8 (Comma delimited)"
  • In Google Sheets: File > Download > Comma-separated values (.csv)

File too large

Maximum file size is 10 MB. If your file exceeds this:

  • Remove unnecessary columns before uploading
  • Split large datasets into multiple files
  • Consider compressing text columns that contain very long responses

Column not found

When selecting a column to code, make sure:

  • The column has a header row (first row contains the column name)
  • The column name doesn't contain special characters that might cause issues
  • The column actually contains text data (not formulas or references)

Low Kappa Scores

Understanding low scores

A low Cohen's Kappa score (below 0.40) indicates poor agreement between the AI raters. This can happen for several reasons:

Possible Cause Solution
Ambiguous categories Review your category definitions and make them more specific
Overlapping categories Ensure categories are mutually exclusive or use multi-label mode
Vague descriptions Add concrete examples to your category descriptions
Domain-specific language Add training data with examples from your specific domain
Too many categories Consider consolidating similar categories

Improving accuracy

  1. Review disagreements: Go through the reconciliation queue to see where raters disagree
  2. Look for patterns: Are disagreements concentrated in certain categories?
  3. Refine descriptions: Update category descriptions to address common confusion points
  4. Add training data: Include reconciled examples as training data for future runs
  5. Re-run: Run again with the improved guide and training data

Iterative improvement: It's normal to refine your coding guide over multiple runs. Academic coding schemes are typically developed through multiple rounds of pilot testing.

Credit Issues

Insufficient credits

If you don't have enough credits to start a coding run:

  • Check your credit balance in the top navigation bar
  • Try using a lower model tier (Budget instead of Standard or Quality)
  • Run a smaller subset of your data first
  • Purchase additional credits from the Credits page

Credits not refunded for cancelled run

When you cancel a coding run:

  • Credits for unprocessed responses are automatically refunded
  • Credits for already-processed responses are not refunded (processing already occurred)
  • The refund appears in your balance immediately
  • Check your credit transaction history in Settings for details

Unexpected credit usage

Credit usage depends on several factors:

  • Model tier: Budget (1x), Standard (1.5x), Quality (3x)
  • Training data: Larger training datasets slightly increase costs
  • Response count: Unclassifiable responses (empty, gibberish) are not charged

Check before running: The cost estimate shown before starting a run accounts for all these factors. Review it to avoid surprises.

Coding Run Failures

Run stuck at "Processing"

If a run appears stuck:

  • Large datasets (1000+ responses) take longer to process
  • Check the progress percentage - if it's changing, the run is still active
  • Wait at least 5 minutes before assuming there's an issue
  • If truly stuck, refresh the page and check the run status again

Run failed with error

If a run fails completely:

  • Credits for unprocessed responses are automatically refunded
  • Check the error message for specific details
  • Common causes: invalid coding guide configuration, API rate limits
  • Try running again after a few minutes

Partial results

If a run completes but some responses show errors:

  • Individual response errors don't fail the entire run
  • Check which responses failed in the results view
  • Common causes: extremely long responses, unusual characters
  • You can re-run just the failed responses

Export Issues

Export file is empty

Check that:

  • The coding run completed successfully
  • There are classified responses (not all were unclassifiable)
  • You selected the correct export format

Missing columns in export

Export includes different columns depending on the format:

  • Full export: All columns including both rater outputs and confidence scores
  • Summary export: Just the final classification and agreement status
  • See Export Formats for complete details

Account Issues

Can't log in

  • Check that you're using the correct email address
  • Use the "Forgot password" link to reset your password
  • Clear your browser cache and cookies, then try again

Email verification not received

  • Check your spam/junk folder
  • Add support@qualcode.ai to your contacts
  • Request a new verification email from the Settings page

Getting More Help

If you're still experiencing issues:

  • Check the FAQ for additional answers
  • Contact support at support@qualcode.ai
  • Include details about the issue: what you were doing, any error messages, your browser/device