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Checking VDatum Offshore with Bottom Mounted Pressure Gauge Geodetically Referenced with GNSS ASV

2023· article· en· W4389543721 on OpenAlexaff
Uchenna C. Nwankwo, Johnson O. Oguntuase, Stephan Howden, David Wells

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeodetic datumTide gaugeGNSS applicationsBuoyGeodesySubmarine pipelineGeologySatellite systemSatelliteHydrographySea-surface heightSea levelMeteorologyEnvironmental scienceGeographyEngineeringOceanographyAerospace engineeringAltimeter

Abstract

fetched live from OpenAlex

The United States National Oceanic and Atmospheric Administration has a Vertical Datum Transformation tool (VDatum) that allows for the conversions between tidal, ellipsoid and orthometric vertical datums. These datums are adopted by different agencies for measurements. One important application of the Global Navigation Satellite System (GNSS) is to facilitate for hydrographic surveying to the ellipsoidal datum and using the VDatum tool to reduce the soundings to the Mean Lower Low Water (MLL W) which is a tidal datum. This has resulted in several studies to determine the regions where these large uncertainties prevail. These uncertainties cannot be absorbed by the IHO vertical uncertainty budget for special order through order 1 b. In the previous studies using USGS coastal water level gauges and an offshore buoy, errors in the Great diurnal range (Gt) tidal datum and the topography of sea surface (TSS) were determined in some of the study areas. For the latter case, repeated vandalism of the surface buoy limited the duration of the water level record. In this study, a novel technique was adopted to reduce the chances of vandalism and obtain a minimum 30-day water level record for tidal datum computation. It involved the use of a bottom-mounted pressure gauge, deployed for more than 30 days, and an autonomous surface vehicle (ASV), equipped with both survey grade and low cost global navigation satellite systems (GNSS), deployed for 7 hours, to tie the sea level data to the ellipsoid. In addition to these datasets, oceanographic parameters such as temperature, salinity and density of the seafloor were measured. The CTD and pressure sensor datasets were used to investigate the temporal evolution of these oceanographic parameters including the variabilities in the oceanographic parameters due to the passage of a tropical storm. U sing the hydrostatic balance equation as well as the ellipsoidal height of the sea surface obtained from the ASV, the ellipsoidal height of the sea surface was estimated. Tidal datums were computed using the sea surface ellipsoidal height by applying the modified range ratio technique as described in [1] using the Dauphin Island NOAA water level station as a primary station. The computed tidal datums were compared to VDatum results to determine the fidelity of the VDatum tool in estimating tidal datums over the study area. The results of this study agreed to VDatum outputs within the published VDatum uncertainty of ± 0.17 m.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.005

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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