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Record W6888580021 · doi:10.18739/a2pc2tb3s

Seaglider observations in Davis Strait; 2005-2014

2024· dataset· en· W6888580021 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHydrographyArcticTransectTemperature salinity diagramsThe arcticSalinity

Abstract

fetched live from OpenAlex

The Davis Strait observing system was established in 2004 to advance understanding of the role of Arctic – sub-Arctic interactions in the climate system by collecting sustained measurements of physical, chemical and biological variability at one of the primary gateways that connect the Arctic and subpolar oceans. Efforts began as a collaboration between researchers at the University of Washington’s Applied Physics Laboratory and the Canadian Department of Fisheries and Ocean’s Bedford Institute of Oceanography, but has grown to include researchers from the Greenland Institute of Natural Resources, Greenland Climate Institute, Danish Technological University, University of Alberta and University of Colorado, Boulder. The project is a component of the NSF Arctic Observing and Atlantic Meridional Overturning Networks, and the international Arctic-Subarctic Ocean Flux (ASOF) program, Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP), Global Ocean Acidification Observing Network (GOA-ON), Arctic Monitoring Assessment Programme (AMAP) and OceanSITES system. Seaglider observations of temperature and salinity extending from the surface to a maximum of 1000 meter (m) depth were collected in Davis Strait from 2005-2014. Seagliders made repeat transects across Davis Strait between waypoints near 66°45' North (N), 60°30' West (W) and 67°N, 56°30' W (though these waypoints and the pathway of the gliders between the waypoints varied). Acoustic navigation enabled year-round data collection. This dataset contains 15 files, each of which contains Level 3 data from one Seaglider deployment in Davis Strait. Deployments lasted from 11 to 174 days and had a median duration of 83 days. Files contain several temperature and salinity products: data not interpolated or despiked; data despiked and interpolated to a common depth/time grid; and low-pass filtered data. Files also include quality control (QC) flags. Each file also contains depth-averaged current vectors from the Seaglider flight model and surface current vectors estimated from the Seaglider's drift track. Data files are named as follows: sg _DavisStrait_ _level3.nc Level 2 files containing individual dive data are available by contacting the dataset creator. More details about the project can be found at https://iop.apl.washington.edu/project.php?id=davis.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.328
Threshold uncertainty score0.651

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.037
GPT teacher head0.303
Teacher spread0.266 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

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