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Record W7115707263 · doi:10.25976/dgx6-1f31

Arctic River Delta Experiment (ARDEX) water quality, 2004.

2025· dataset· en· W7115707263 on OpenAlexaboutno aff

Bibliographic record

VenueDataStream · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsArcticPermafrostEstuaryRiver deltaDeltaSubmarine pipelineWater qualityColored dissolved organic matterHydrology (agriculture)

Abstract

fetched live from OpenAlex

The Arctic River Delta EXperiment (ARDEX) was a 2004 satellite program of the CASES (Canada Arctic Shelf Exchange Study) program designed to extend offshore measurements of CASES into the freshwater-saltwater transition zone of the Mackenzie River estuary and delta. The objectives of ARDEX were to evaluate the properties of dissolved organic matter (DOM) in the river and coastal waters, and the photochemical, geochemical and biological processes regulating DOM dynamics. This dataset was a portion of the ARDEX project investigating how general water quality, DOM, and nutrients changed across the freshwater-saltwater transition zone. We demonstrated that DOM character, nutrients, and general water quality changed considerably across the transition zone with implications for marine ecosystem health. Water sampling occurred during the 2004 summer from a coast guard vessel travelling north from Inuvik to the Beaufort Sea. This research was funded by the Natural Sciences and Engineering Research Council of Canada, with support from the Canada Research Chair Program, Polar Continental Shelf Project, and the Northern Scientific Training Program. We appreciate technical and logistical support from the Inuvik Research Center/Aurora Research Institute, Indigenous and Northern Affairs Canada, and Water Survey of Canada.

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)0.002
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.276
Threshold uncertainty score0.549

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.008

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 head0.030
GPT teacher head0.342
Teacher spread0.312 · 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
Published2025
Admission routes1
Has abstractyes

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