Zooplankton picked from a sediment trap (400 m depth) at the P3 observation site, Northeast Scotia Sea, throughout 2018
Bibliographic record
Abstract
Here, for the first time in the Southern Ocean, this dataset contains the seasonal occurrence of the zooplankton assemblage in the Northeast Scotia Sea using a sediment trap deployed throughout 2018 (P3 observation site, 52.80 degrees S, 40.14 degrees W). Southern Ocean zooplankton provide globally significant ecosystem services through their role in carbon sequestration, nutrient cycling and food webs. The remote and extreme nature of the Southern Ocean creates significant logistical difficulties for studying zooplankton all year round and there is a significant paucity in winter data. Sediment traps are able to sample throughout the year, providing much needed insight into the seasonality of zooplankton in the Southern Ocean. The dataset is accompanied by temperature data at depth 200 m from the CTD instrument mounted on the P3 observation site mooring. Clara Manno was supported by UK Research and Innovation Future Leaders Fellowships project CUPIDO (MR/T020962/1). Work was carried out as part of the Ecosystems programme at the British Antarctic Survey and the Scotia Sea Open Ocean Laboratories (SCOOBIES) sustained observation programme at the British Antarctic Survey in the frame of a Western Core Box-POETS survey cruise (https://www.bas.ac.uk/project/scoobies/).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.013 |
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".