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Record W1873432389 · doi:10.1139/er-2013-0073

A review of developments in ballast water management

2014· review· en· W1873432389 on OpenAlexvenueno aff
Rajoo Balaji, Omar Yaakob, Kho King Koh

Bibliographic record

VenueEnvironmental Reviews · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsnot available
FundersMinistério da Ciência, Tecnologia e Inovação
KeywordsBallastRatificationSustainabilityPort (circuit theory)EngineeringBusinessEnvironmental planningEnvironmental resource managementEnvironmental science

Abstract

fetched live from OpenAlex

Transportation and translocation of non-native species by ships through ballast water is one of the current issues the shipping industry is trying to address. The Ballast Water Convention is nearing full ratification after which treatment of ballast water will become mandatory for most of the trading merchant vessel categories. Ballast water management systems employing various technologies are commercially available but at high costs. Economics apart, the efficiency of these technologies and realistic ways to ensure compliance with stricter requirements of some Administrations are issues that need to be focussed upon. With the report of the Environmental Protection Agency as an assessment reference, this paper reviews the treatment technologies. Juxtaposing reports of Lloyd’s Register on the status, a concise overview of the technologies has been projected. A sustainable ballast water management based on data and assessments is proposed. The management must be extended to both shore and on-board platforms for practices, treatment, sampling, testing, and recycling. An exemplar system harvesting shipboard waste heat is projected as a route for thermal treatment in combination with technologies showing potential for optimized ballast water management.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.016

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 head0.023
GPT teacher head0.271
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations43
Published2014
Admission routes1
Has abstractyes

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