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Record W1995197227 · doi:10.1029/01eo00004

Software simplifies air‐sea data estimates

2001· article· en· W1995197227 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEos · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAtmosphere (unit)Coupling (piping)SoftwareBoundary (topology)Computer scienceMeteorologyFlux (metallurgy)Environmental scienceBoundary layerWork (physics)ClimatologyGeologyGeographyAerospace engineeringMathematicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The atmosphere and oceans interact at the ocean surface through boundary layers that are millimeters to many tens of meters thick. Processes at work in this relatively thin region are crucial in controlling the coupling between air and ocean and, as such, are important both in studies of the ocean or atmosphere in isolation, and in studies of the coupled system that investigate—for example—interannual climatic variability However, as a practical matter, attempts to generate flux estimates from particular observational data sets often involve a great deal of effort, since the relevant parameterizations are scattered throughout the literature; may have only limited applicability to certain locations and regimes; and are found using algorithms that are often complex and iterative. This can be especially frustrating when boundary layer theory is only peripheral to the main scientific or educational interest.

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.074
GPT teacher head0.275
Teacher spread0.201 · 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