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Record W7014662266

Predicting tidal heights for new locations using 25 hours in situ sea-level observations plus reference site records: a complete tidal species modulation with tidal constant.

2015· article· en· W7014662266 on OpenAlexfundno aff

Bibliographic record

VenueUniversity of Canterbury Research Repository (University of Canterbury) · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersDivision of Ocean SciencesFisheries and Oceans Canada
KeywordsCalibrationWork (physics)Long-term predictionSampling (signal processing)Process (computing)Stability (learning theory)
DOInot available

Abstract

fetched live from OpenAlex

A hybrid technique for predicting tides for new locations, based on as little as 25 h of concurrent temporary and reference site sea level observations, plus up to a year of reference records, is evaluated using 2-yr South Korean and New Zealand case studies. Comparisons are made between the existing prediction methods of conventional standard harmonic analysis and prediction (CSHAP) and tidal species modulation with tidal constant corrections (TSM1TCC). Building on these approaches, a new procedure is developed to produce a complete tidal species modulation (CTSM) equivalent of CSHAP, with the added inclusion of nodal factors and angles, astronomical arguments, and tidal species tidal constant correction terms (1TCC), to generate results for temporary sites. The CTSM1TCC approach described here overcomes the record length limitations of traditional standard harmonic-based prediction methods, making the technique more useful to diverse coastal and hydrographic researchers. The CTSM1TCC method is refined using yearlong input and comparative data from contrasting hydrographic settings, revealing spring periods, specific months, and conditions devoid of nontidal residual extremes (e.g., storms) as the most appropriate sample periods for collecting temporary site data in order to maximize prediction accuracy. CTSM1TCC represents a viable alternative to tidal prediction methods using multiconstituent inferences, for those wishing to make predictions for new sites based on established conventional tidal prediction software, with the added benefits of efficient input data collection and no need for a decision process regarding multiconstituent inference calculations. CTSM1TCC could, without compromising accuracy, support the spatial and temporal proliferation of tidal predictions across coastal oceans, where fieldwork funds and instruments currently hinder predictions for new locations.

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)0.002
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 score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.155
GPT teacher head0.253
Teacher spread0.098 · 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
Published2015
Admission routes1
Has abstractyes

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