Taxonomic and genetic diversity of Decapods in Northeast Pacific, Canadian Arctic and Northwest Atlantic : an exploratory project under the DFO–NOAA/NMFS climate and fisheries collaboration
Bibliographic record
Abstract
An exploratory project on the taxonomic and genetic diversity of decapods sampled in 2022 in three ocean subregions (Northeast Pacific, Canadian Arctic, and Northwest Atlantic) was undertaken by the Arctic Working Group as part of Canada–U.S. Collaboration on Climate and Fisheries, specifically between Fisheries and Oceans Canada (DFO) and the National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric Administration (NOAA). This collaboration framework aims to pool Canadian and U.S. data to explore the impacts of broad-scale climate change on marine biodiversity. First, the identification of the specimens (n = 995) received from collaborators was reviewed in the laboratory. The highest correction rate was found for specimens from the Bering Sea region. In a second step, genetic analyses on the COI DNA barcodes were carried out on a selection of 19 species (87 specimens). Problematic assignments of scientific names obtained from public repositories (BOLD, NCBI-nt) for the genera Eualus, Hyas, and Pandalus are discussed. In summary, this project highlights the need to review the scientific names used in various datasets before performing analyses of biodiversity data as well as the need to carry out phylogenetic research (taxonomic and genetic) on certain taxa that show interesting species complex issues (especially Lebbeus polaris and Spirontocaris spinus).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".