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Record W2185805257

OCEAN FRONTS AROUND ALASKA FROM SATELLITE SST DATA

2003· article· en· W2185805257 on OpenAlexaboutno aff
Igor M. Belkin, Peter Cornillon, David Ullman

Bibliographic record

VenueSeventh Conference on Polar Meteorology and Oceanography and Joint Symposium on High-Latitude Climate Variations · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyGeologySea surface temperatureFront (military)Cold frontClimatologySatelliteCurrent (fluid)PlumeGeographyMeteorology
DOInot available

Abstract

fetched live from OpenAlex

Long-term time series of satellite observations are used to survey ocean surface thermal fronts in the Gulf of Alaska, Bering, Chukchi and Beaufort Seas as well as in the upstream region of the Alaskan Current and farther south along the North American shelf to include British Columbia waters and the Columbia River Plume area, thus covering 45°N-75°N, 160°E-120°W. The Cayula-Cornillon algorithms for front detection and cloud screening were applied to the Pathfinder twice-daily 9-km resolution SST images from 1985-1996. A number of new frontal features have been identified in the Alaskan Seas; some previously known fronts have been systematically studied for the first time. Frontal frequency maps are provided for each of four Alaskan Seas. In the Gulf of Alaska and Bering Sea the SST fronts are best defined in spring (May) and fall (November), while being masked by surface heating in summer. In the Chukchi and Beaufort Seas the SST fronts are best seen in summer (August-September), when both seas are typically ice-free. Seasonal evolution of SST fronts is noted off the OregonWashington coasts and Vancouver Island, in Hecate Strait and Dixon Entrance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.227
Teacher spread0.202 · 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

Citations22
Published2003
Admission routes1
Has abstractyes

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Same venueSeventh Conference on Polar Meteorology and Oceanography and Joint Symposium on High-Latitude Climate VariationsSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207