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Record W1981565127 · doi:10.1029/2005jc003159

Winter water masses in the Gulf of St. Lawrence

2006· article· en· W1981565127 on OpenAlexaffabout
Peter S. Galbraith

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsHydrographyOceanographyTrough (economics)SalinityGeologyTemperature salinity diagramsDeep waterWater massClimatologyVolume (thermodynamics)Environmental science

Abstract

fetched live from OpenAlex

The first 9 years of data collected during a new late wintertime hydrographic survey of the Gulf of St. Lawrence are presented. They show colder conditions than those previously measured from ships that were likely biased toward warmer ice‐free waters. The total volume of cold water (<−1°C) varied interannually from 10 to 15 × 10 3 km 3 and is a good predictor for the following summertime Cold Intermediate Layer index. The volume of cold and saline Labrador Shelf waters that flowed in through the Strait of Belle Isle is estimated using two temperature‐salinity criteria. It exhibits much stronger interannual variability than the total cold water volume, representing from 5% to as much as 30% of all cold surface waters. It was sometimes observed to reach the bottom in Mecatina Trough at more than 200 m depth, where deep waters are isolated from the rest of the gulf.

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 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 score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.281
Teacher spread0.259 · 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

Citations107
Published2006
Admission routes2
Has abstractyes

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