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The Evaluation of Salinity Measurements from PALACE Floats

2001· article· en· W2108221229 on OpenAlexaboutno aff
Sheldon Bacon, Luca Centurioni, W.J. Gould

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsSalinityTemperature salinity diagramsEnvironmental scienceFloat (project management)ConductivityGeologyStructural basinMeteorologyOceanographyOcean currentClimatologyRemote sensingMarine engineeringGeographyPhysicsGeomorphology

Abstract

fetched live from OpenAlex

Seven PALACE (Profiling Autonomous Lagrangian Circulation Explorer) floats were deployed in October 1996 in the Irminger Basin of the Atlantic Ocean as a U.K. contribution to the World Ocean Circulation Experiment. Of these floats, four were fitted with a conductivity–temperature–depth package. The floats were ballasted to drift at a depth of about 1500 m, above the Labrador Sea Water (LSW) cold and fresh extreme, and programmed to surface every 14 days. The floats made a profile during each ascent to the surface. The authors present a method to evaluate the performance of the conductivity sensors and to calibrate the float salinity data. Since the LSW appears to be relatively stable over a timescale of ∼1–2 months and a length scale of ∼50–100 km, the authors were able to make direct comparisons between the first year of float data and accurate ship-based measurements and, therefore, were able to correct for errors of the conductivity sensors. A correction was applied in all cases. The conductivity sensors were all stable within, or very close to, the manufacturer's specification, with a maximum drift for salinity of (0.0009 ± 0.0004) month−1.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.251
Teacher spread0.221 · 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

Citations21
Published2001
Admission routes1
Has abstractyes

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