MétaCan
Menu
Back to cohort
Record W4410840400 · doi:10.1061/9780784486146.005

Advanced Mooring Analysis—Matarani Port, Peru

2025· article· en· W4410840400 on OpenAlexaff
Jeff Oskamp, Patricio Monárdez, Paul Knox

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsPort (circuit theory)MooringMarine engineeringComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Terminal Internacional Del Sur S.A. (TISUR) is undertaking a port expansion project at Matarani Port, Peru. The port is subject to moderate swell wave activity, which is reflected by the steep rock shoreline and strongly influenced by a nearby island. This paper outlines how both physical and numerical modeling efforts were used to better understand the wave conditions in the port, optimize the design of the breakwater, and make recommendations for optimizing the mooring system design. This project provides an example of how numerical and physical modeling can be used to complement each other.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.003
GPT teacher head0.197
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicWave and Wind Energy SystemsFrench-language works237,207