anchor.diff:              includedSuggestions.isNotEmpty) {
             final relevance = high--;
             completionSuggestions.forEach((completionSuggestion) {
  -            completionSuggestion.relevance = relevance;
  +            completionSuggestion.relevance =
  +                relevance + _BASE_RELEVANCE_COMPENSATION;
             });
             includedSuggestions.forEach((includedSuggestion) {
  -            includedSuggestion.relevanceBoost = relevance - _MAX_BASE_RELEVANCE;
  +            includedSuggestion.relevanceBoost = relevance;
             });
           } else {
             suggestions
  
positive.code:           includedSuggestions.isNotEmpty) {
          final relevance = middle--;
          completionSuggestions.forEach((completionSuggestion) {
            completionSuggestion.relevance = relevance;
          });
          includedSuggestions.forEach((includedSuggestion) {
            includedSuggestion.relevanceBoost = relevance - _MAX_BASE_RELEVANCE;
          });
        } else if (!isRequestFollowingDot) {
          suggestions
              .add(createCompletionSuggestion(entry.key, featureSet, low--));
        }
      });
  
  
negative.code: /// Number of lookback tokens.
  const int _LOOKBACK = 100;
  
  /// Completions coming from an [AvailableSuggestionSet] receive
  /// a base relevance between 0 and 8 which their relevanceBoost
  /// gets added on top of. Give classic completion suggestions
  /// a moderate base boost of 4 to compensate.
  const int _BASE_RELEVANCE_COMPENSATION = 4;
  
  /// Minimum probability to prioritize model-only suggestion.
  const double _MODEL_RELEVANCE_CUTOFF = 0.5;
  