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Record W2980154854 · doi:10.1109/ccece.2019.8861931

Evaluation of Unsteady Wave Influence on Tidal Stream and Mitigation Strategy

2019· article· en· W2980154854 on OpenAlexaff
Ali Fituri, Hamed H. Aly, M.E. El-Hawary

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTidal powerMarine energyStream powerPower (physics)Environmental scienceMarine engineeringWave powerEnergy (signal processing)Work (physics)Reduction (mathematics)Wind waveMeteorologyElectric power systemGeologyOceanographyEngineeringErosionPhysics

Abstract

fetched live from OpenAlex

Marine energy is getting more attention recently as it deems a huge source of clean power. Tidal power is the most promising image of marine and ocean energy due to the high accurate prediction of the available power and cutting-edge control system design with new cost reduction strategies. The aim of the work is to mitigate the behavior of surface ocean waves under severe weather condition. The presence of unsteady waves influences the overall performance of in-stream tidal power system. Such effect may appear as a fluctuation in the output power or reduction in the produced energy. In this paper, the data of wave height and tidal speed was taken from Minas passage and used to mitigate the wave effect on the stream power system.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.199

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)0.0000.000

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 head0.019
GPT teacher head0.227
Teacher spread0.208 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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