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Record W2511183000 · doi:10.1038/sdata.2016.70

Mean hydrography on the continental shelf from 26 repeat glider deployments along Southeastern Australia

2016· article· en· W2511183000 on OpenAlexaff
Amandine Schaeffer, Moninya Roughan, Tim Austin, Jason D. Everett, David A. Griffin, Ben Hollings, E.L. King, Alessandra Mantovanelli, Stuart Milburn, B. Pasquer, Charitha Pattiaratchi, Robin Robertson, Dennis Stanley, Iain M. Suthers, Dana White

Bibliographic record

VenueScientific Data · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsOcean Networks Canada Society
FundersAustralian Government
KeywordsContinental shelfOceanographyHydrographyGliderGeologyBoundary currentStratification (seeds)Continental marginUpwellingOcean currentWater massCurrent (fluid)Paleontology

Abstract

fetched live from OpenAlex

Since 2008, 26 glider missions have been undertaken along the continental shelf of southeastern Australia. Typically these missions have spanned the continental shelf on the inshore edge of the East Australian Current from 29.5-33.5°S. This comprehensive dataset of over 33,600 CTD profiles from the surface to within 10 m of the bottom in water depths ranging 25-200 m provides new and unprecedented high resolution observations of the properties of the continental shelf waters adjacent to a western boundary current, straddling the region where it separates from the coast. The region is both physically and biologically significant, and is also in a hotspot of ocean warming. We present gridded mean fields for temperature, salinity and density, but also dissolved oxygen and chlorophyll-a fluorescence indicative of phytoplankton biomass. This data will be invaluable for understanding shelf stratification, circulation, biophysical and bio-geochemical interactions, as well as for the validation of high-resolution ocean models or serving as teaching material.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptno category
Domain: not available · Genre: Dataset
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.006

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 head0.055
GPT teacher head0.241
Teacher spread0.186 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Not applicable
Domainnot available
GenreEmpirical · Dataset

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

Citations16
Published2016
Admission routes1
Has abstractyes

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