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Record W2142744137 · doi:10.5539/jsd.v5n12p19

Development of a Green Floating Breakwater with Re-use of PET Bottles

2012· article· en· W2142744137 on OpenAlexvenueno aff
Luana Kann Kelch Vieira, Tiago Zenker Gireli

Bibliographic record

VenueJournal of Sustainable Development · 2012
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
FundersUniversidade de São Paulo
KeywordsReuseBreakwaterShoreSustainable developmentCoastal erosionEnvironmentally friendlyBusinessHumanityResource (disambiguation)Environmental planningEnvironmental resource managementEnvironmental scienceArchitectural engineeringWaste managementEngineeringComputer scienceGeologyEcologyPolitical scienceOceanographyLaw

Abstract

fetched live from OpenAlex

It is common sense that the ongoing climate changes represent a big challenge to humanity to protect housing, industries, nature and lives. This causes changes in strategies and in the conception of development and growth. Thinking is changing; the planet has to be preserved and protected not only its resources explored. All industries are engaged in this cause and so is construction. This article presents and alternative specifically for sustainable construction in coastal protection. Coastal engineering is constantly developing new projects in turn of shore protection and also to contribute positively to the environment. Despite climate changes, the development of industries and modern lifestyle generate tons of waste every year and, as result, it has to be disposed and treated. One way of reducing the amount of waste that goes into the environment is to reuse disposed items. Another way of reusing plastic bottles, a significant part of Brazil’s domestic waste, is presented and in a different application as commonly found: in coastal engineering. The breakwater that is being developed, consumes millions of bottles depending on the extension of the shore protection arrangement. The construction of the green breakwater is environmentally friendly due to the inert materials that will are used. This concept is under development and research but the physical model was built and tested. It consumed 1260 bottles for its construction and pointed to important issues and questions that have to be addressed during the ongoing project.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.589

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 head0.012
GPT teacher head0.197
Teacher spread0.185 · 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 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

Citations3
Published2012
Admission routes1
Has abstractyes

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