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Record W2046247595 · doi:10.1109/igarss.2012.6350391

Does modis sea surface temperature accurately represent the temperature of the dynamically significant surface layer of the ocean?

2012· article· en· W2046247595 on OpenAlexafffund
Meghan G. Lobb, Joseph R. Buckley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsRoyal Military College of Canada
FundersCanadian Space AgencyMinistère de la Défense Nationale
KeywordsArgoSea surface temperatureEnvironmental scienceClimatologyDaytimeMeteorologyAtmospheric sciencesRemote sensingGeologyGeography

Abstract

fetched live from OpenAlex

This paper describes a comparison between ocean skin temperature as estimated by MODIS 11μm radiation in both day and night overpasses, and near-surface measurements made by Argo buoys co-located in time and space with MODIS pixels located in two 20° × 20° regions in the eastern Pacific Ocean, for the period 2003-2010. On average, Argo temperatures were warmer than MODIS temperatures, by about 0.3°C on average in the daytime, and 0.8°C at night. There was significant month-to-month variation in these relationships, but little interannual variability. In general, the measurements are not directly interchangeable within established limits of uncertainty for SST measurements, but are when the mean monthly differences are taken into account. The mean differences themselves provide useful information on the relationship between ocean skin temperature and that a few metres below the surface.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.216
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2012
Admission routes2
Has abstractyes

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