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Record W2155612666 · doi:10.1002/2014gl061241

Continental microseismic intensity delineates oceanic upwelling timing along the west coast of North America

2014· article· en· W2155612666 on OpenAlexaff
Richard E. Thomson, M. Heesemann, Earl E. Davis, Roy A. S. Hourston

Bibliographic record

VenueGeophysical Research Letters · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsOcean Networks Canada SocietyUniversity of VictoriaGeological Survey of CanadaFisheries and Oceans Canada
FundersU.S. NavyNational Oceanic and Atmospheric Administration
KeywordsUpwellingDownwellingOceanographyMicroseismGeologySubmarine pipelineContinental shelfClimatologyWind stressClimate changeProductivitySeismology

Abstract

fetched live from OpenAlex

Abstract The biological productivity of coastal upwelling regions undergoes marked interannual variability as marine ecosystems respond to changes in the prevailing winds. Determination of the principal metrics that define the upwelling cycle—the spring transition, when ocean conditions switch from downwelling‐ to upwelling‐favorable, and the Fall Transition, when conditions return to downwelling‐favorable—is essential for understanding changes in coastal productivity. Here we demonstrate that upwelling in the northern California Current System may be delineated by changes in microseismic activity recorded at a broadband seismological station in southwestern British Columbia. Observed high correlation between microseismic intensity and offshore bottom pressure fluctuations at ~0.2 Hz confirms a direct link to regional wind‐wave generation. Comparison of transition times derived from coincident 20 year records of microseismic intensity and alongshore wind stress for the British Columbia‐Oregon coast suggests that seismically derived times may be more representative of coastal upwelling than times derived using traditional methods.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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.

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

Citations23
Published2014
Admission routes1
Has abstractyes

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