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Record W2510124594

A GLOBAL WAVE ENERGY RESOURCE ASSESSMENT

2008· article· en· W2510124594 on OpenAlexafffundvenue
Andrew Cornett

Bibliographic record

VenueNPARC · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsNational Research Council Canada
FundersNatural Resources Canada
KeywordsBuoyWind wave modelMeteorologyEnergy (signal processing)Environmental scienceResource (disambiguation)Wave heightWave modelSignificant wave heightClimatologyComputer scienceWind waveGeologyWind speedGeographyStatisticsMathematicsOceanography
DOInot available

Abstract

fetched live from OpenAlex

This paper presents results from an investigation of global wave energy resources derived from analysis of wave climate predictions generated by the WAVEWATCH-III (NWW3) wind-wave model (Tolman, 2002) spanning the 10 year period from 1997 to 2006. The methodology that was followed to obtain these new results is described in detail. The spatial and temporal variations of the global wave energy resource are presented and described. Several parameters to describe and quantify the temporal variation of wave energy resources are presented and discussed. The new results are also validated through comparisons with energy estimates from buoy data and previous studies.

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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.209
Teacher spread0.192 · 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

Citations304
Published2008
Admission routes3
Has abstractyes

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