First characterization of the marine ecosystem of Archer Fiord in the Lasting Ice Area of the High Arctic: a productivity paradox
Bibliographic record
Abstract
The Lasting Ice Area along the northern coastline of Ellesmere Island and Greenland will be the region where Arctic multiyear sea ice will persist the longest in a warming climate, making this area critical for ice-dependent species. In 2019, the Tuvaijuittuq Marine Protected Area was established for the interim protection of the waters off northern Ellesmere Island. We present the first comprehensive study of the Archer Fiord–Lady Franklin Bay system located at the northern end of Nares Strait, in the Tuvaijuittuq area. Data on the hydrography, biogeochemical cycles, pelagic and benthic productivity, and seabed sediment were collected along a nearshore-offshore transect. The region is influenced by meteoric waters as well as Pacific and Atlantic-derived waters, and likely acts as a strong seasonal CO 2 sink. Despite fall-bloom conditions, low primary, secondary, and benthic productivity contrasted with the relatively high abundance of marine mammals. This productivity paradox either suggests (1) that organic matter and detritus deposited and accumulated over long periods prior to our survey sustain the benthic community on which marine mammals depend for foraging; (2) local productivity hotspots in areas outside the sampled stations; or (3) a highly efficient system with minor production surpluses. Solving this paradox will require further surveys in the area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".