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Record W7005832756

Sea surface circulation in the straits of Malacca and the andaman sea using twenty-three years satellite altimetry data

2018· other· en· W7005832756 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Repository (Petra Christian University) · 2018
Typeother
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsDrifterAltimeterTide gaugeSea-surface heightOcean currentOcean surface topographySatellite altimetrySatelliteCirculation (fluid dynamics)
DOInot available

Abstract

fetched live from OpenAlex

The ocean circulation in the Straits of Malacca is derived using the satellite altimeter data from January 1993 until 2015. The satellite altimeters are TOPEX, Jason-1, Jason-2, ERS-1, ERS-2, Envisat, SARAL, and Cryosat. The sea surface height derived from the satellite altimeter has been very useful in the study of the ocean circulation but still is not appropriate for the oceanographic application. This is because it is a superposition of geophysical effect such as the tidal effect. The tidal models are more suitable to be used in the open sea like the South China Sea. The tidal effect is rather complex to be determined, especially in a shallow water area like the area in the Strait of Malacca. In order to remove the tidal effect, the best ocean tide model needs to be examined to determine the ocean circulation in the Straits of Malacca. To verify the result, the sea level anomaly (SLA) data were compared to the tide gauge data and the pattern obtained are regularly the same. In order to check the ocean circulation using the altimetric data, the result was compared with the trajectories drifter from Marine Environmental Data Station (MEDS) of Canada. The trajectories of the drifter have confirmed that the current pattern around studied region during June 9, 1999 until July 9, 1999.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.648

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.051
GPT teacher head0.268
Teacher spread0.217 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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