RELATIONSHIP BETWEEN WATER PROPERTIES AND PLANKTONIC FORAMINIFERAL STABLE ISOTOPES FROM SURFACE SEDIMENTS IN WESTERN ARCTIC OCEAN
Bibliographic record
Abstract
Planktonic foraminifer species Neogloboquadrina pachyderma (sin.) is widely used in paleoceanographic studies in the Arctic Ocean. However, studies on this species are mainly in the eastern Arctic Ocean. N. pachyderma (sin.) from 32 western Arctic Ocean surface sediment samples collected by the First and Second Chinese Arctic Expedition were analyzed for stable oxygen and carbon isotopes. In this paper we try to establish the relationship between the Delta~(18)O, Delta~(13)C and water properties. Studies on N. pachyderma (sin.) indicate that this species mainly lives between 30 to 100 m water depth in western Arctic Ocean Delta~(18)O records of this species in the Chukchi Sea indicate the variations of water temperature and salinity, while in the Chukchi Plateau and eastern Northwind Ridge Canadian Basin, they mainly indicate the salinity difference. Delta~(13)C records of this species reflect the nutrient level of the water mass. Heavy Delta~(13)C in central Chukchi Sea and eastern Northwind Ridge Canadian Basin reveals the low nutrient usage in this area, while light Delta~(13)C in the Chukchi Plateau and Northwind Ridge indicates nutrient-poor environment in this area.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".