On the terrestrial and freshwater invertebrate diversity of the High Arctic archipelago of Svalbard: a revised species inventory and synopsis of the community composition
Bibliographic record
Abstract
Arctic terrestrial invertebrate biodiversity is generally poorly known, but the archipelago of Svalbard has one of the most up-to-date inventories of its terrestrial and freshwater faunas of any Arctic region, offering a baseline for long term monitoring of invertebrate communities in space and time. Since the most recent review of the Svalbard invertebrate fauna was produced in 2014, knowledge of this fauna has developed and this inventory is here critically revised and updated. Our aims are (1) to critically review the inventory based on current taxonomic knowledge, (2) publish the complete species inventory, including cross-referencing to the relevant publications, in an open access data archive (GBIF), and (3) highlight the particular advantages that working in Svalbard may bring for scientists working on terrestrial, freshwater, and cryospheric environments. The inventory contains a total 1091 valid species names or interim names. A gap analysis in the Barcode of Life Data Systems reveals that 50% of the species currently documented from Svalbard lack COI (Cytochrome c oxidase subunit 1) barcode reference sequences in this database. Gaps in our knowledge of the Svalbard fauna and how these may be resolved are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".