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Record W4414491807 · doi:10.1080/07055900.2025.2552478

Variability of Surface Currents over Central Juan de Fuca Strait

2025· article· en· W4414491807 on OpenAlexaffvenue
Patrick F. Cummins

Bibliographic record

VenueATMOSPHERE-OCEAN · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSurface (topology)Current (fluid)Channel (broadcasting)Indian ocean

Abstract

fetched live from OpenAlex

Four years of surface currents from a two-element array of high frequency (HF) radars are used to study variability of the regional estuarine circulation over central Juan de Fuca Strait. Surface currents in the long term mean are directed in a seaward outflow to the continental shelf. This outflow is subject to substantial variability on time scales ranging from tidal to interannual, and includes a pronounced seasonal cycle. The integrated along-strait surface-layer transport is used characterize the strength of the sub-tidal circulation. Variability of the transport includes marked reversals of the estuarine outflow that occur primarily during winter and are related to downwelling winds over the outer coast with a time lag of 3 to 4 days. Notably, the surface-layer transport is subject to a seasonal modulation with an approximately three-fold increase in the outflow from winter to summer. Over a wide range of frequencies, the transport is coherent with cross-strait sea-level differences derived from tide gauge data. At the lowest resolved frequencies, including the annual cycle, the surface-layer transport is in approximate geostrophic balance with cross-strait sea-level differences. On interannual time scales, the integrated surface-layer transport during summer appears to respond to variations in the net fresh water runoff due to the spring freshet of the Fraser River, although the record length is too short to draw firm conclusions regarding this dependence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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 routes2
Has abstractyes

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Same venueATMOSPHERE-OCEANSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207