Datasets:
QT26-QC canonical evaluation protocol
Submission
Submit one TSV row per public_id with columns public_id, top1, ..., top20.
Prediction values are FishBase 25.04 canonical_taxon_key strings. All 6,719
canonical IDs must occur exactly once.
If several submitted labels map to the same canonical key, duplicate canonical keys are removed and later distinct keys shift forward. A top-k submission must therefore supply at least k distinct canonical guesses after mapping. Invalid, unmapped or blank predictions occupy the fixed denominator and score as wrong; rejection and structural non-support are also errors.
Metrics
- Primary: query-micro top-1 and species-macro top-1.
- Secondary: query-micro and species-macro top-5 and top-20.
- Paired comparisons: wrong-to-right, right-to-wrong and net-correct counts.
- Uncertainty: 20,000 target-species-cluster bootstrap replicates.
Query-micro weights every query equally. Species-macro first averages within each target taxon and then weights taxa equally. Scores are fractions in the JSON output; multiply by 100 for percent.
Taxonomy mapping
Outputs from another label system must be mapped to FishBase 25.04 before submission. Accepted names, synonyms and finer ranks that resolve to one species should map to one canonical key. If no defensible mapping exists, retain an unmapped token; do not drop the query.
Reference results
reference-baselines.tsv records frozen COVER-Fish configurations as reference
baselines, not state of the art. The Fishial comparison in the paper is confined
to its shared 775-name task and is not a full-roster QT26-QC baseline.
Example
python evaluation/score.py predictions.tsv --output metrics.json
python evaluation/score.py new.tsv --compare old.tsv --output paired.json