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Record W7104256124 · doi:10.14286/yomjsh

Svalbard Tracking Project

2025· dataset· en· W7104256124 on OpenAlexaff

Bibliographic record

VenueOcean Tracking Network · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsOcean Tracking Network
Fundersnot available
KeywordsFjordArcticTracking (education)The arcticTracking systemRecreationCitizen scienceClimate change

Abstract

fetched live from OpenAlex

This is the OBIS extraction of the Ocean Tracking Network and Norwegian Research Centre (NORCE) Svalbard Tracking Project, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=V2LSVAL).Abstract:The Arctic naturally has few endemic fish species but this is changing rapidly due to climate change. The immigration of new species in Svalbard is ongoing and yet there is limited capacity to track the consequences of this change, which is affecting the conservation of endemic Arctic fish while creating new opportunities for commercial and recreational fisheries. We intend to establish an acoustic telemetry infrastructure in Svalbard for tracking climate and environmental changes in the fjords and coastal zones, this project represents a pilot that will 1) advance methods and support initial deployments and 2) undertake tracking of Atlantic cod and Atlantic salmon in Isfjorden to establish first knowledge about the movement of cod and salmon in the fjord. The receivers will be connected to adjacent projects with open data sharing to SIOS and Ocean Tracking Network for data archiving and sharing. Collaboration between NORCE and UNIS will support education and capacity building for this technology in the Arctic and development of highly qualified personnel (one MSc and one early career researcher at NORCE). The project will be used to leverage additional funding for longer-term and larger-scale tracking research from the Norwegian Research Council, Biodiversa, Horizon Europe, and NordForsk to achieve a broader understanding of ecosystem and environmental change in the Arctic. Ultimately, the results are envisioned to provide the Governor of Svalbard with data and tools necessary to manage recreational and commercial fisheries in Svalbard and support marine spatial planning efforts (including marine protected areas)

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.031
GPT teacher head0.308
Teacher spread0.277 · 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
Published2025
Admission routes1
Has abstractyes

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