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Zooplankton picked from a sediment trap (400 m depth) at the P3 observation site, Northeast Scotia Sea, throughout 2018

2024· dataset· en· W6894291637 on OpenAlexaboutno aff

Bibliographic record

VenueNERC Environmental Data Service · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsZooplanktonSediment trapNova scotiaCruiseSedimentPelagic zone

Abstract

fetched live from OpenAlex

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/).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0060.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.388

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.

Opus teacher head0.039
GPT teacher head0.267
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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