review-suggestions

To prioritize species suggestions, you can cross-reference new candidates against existing fixtures to rank them by relationship density, coverage gaps, and connection potential. This process identifies which entries to add, skip, or have already been included.

Cross-referencing species suggestions involves comparing new candidates to current fixtures to detect coverage gaps and rank entries by relationship density. This automated data curation step marks already-added and previously-skipped entries to streamline selection.

Identifying coverage gaps involves analyzing your existing species fixtures against new suggestions to find missing ecological connections. Candidates are then ranked by their potential to bridge these gaps and connect existing species within the dataset.

Yes, you can automate data curation by running a review process that evaluates new species suggestions against current fixtures. The system returns a prioritized recommendation list with rationale and a final action plan for data updates.

Ranking new species candidates by relationship density requires evaluating their potential to connect existing species already present in the fixtures. This highlights candidates that strengthen the ecological network and fill data coverage gaps.

Species suggestions are automatically skipped if they were previously skipped or already added to the fixtures. Cross-referencing against current data ensures these entries are marked appropriately so the review focuses only on viable new candidates.