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Record W3203883919 · doi:10.5772/intechopen.98683

Management of Nutrient-Rich Wastes and Wastewaters on Board of Ships

2021· book-chapter· en· W3203883919 on OpenAlexafffund
Céline Vaneeckhaute

Bibliographic record

VenueIntechOpen eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCruise Tourism Development and Management
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWastewaterEnvironmental scienceSewageWaste managementNutrientFood wasteSewage treatmentEutrophicationAnaerobic digestionEnvironmental engineeringEnvironmental protectionEngineeringEcology

Abstract

fetched live from OpenAlex

Ship-generated nutrient-rich waste sources, including food waste and sewage water, contribute to eutrophication and deoxygenation of marine ecosystems. This chapter aims to discuss the characteristics of these waste and wastewater sources, review current ship-generated organic waste and wastewater regulations, inventory conventional management and treatment practices, and identify future perspectives for more sustainable nutrient-rich waste and wastewater management on board of ships. According to regulations, untreated food waste and sewage can generally be discharged into the open sea at more than 12 nautical miles from the nearest land, hence this is currently a common practice. However, special restrictions apply in special designated areas such as the Baltic Sea, where food waste must be comminuted/grounded and nutrients need to be removed from the sewage prior to discharge at 12 nautical miles from the nearest land. Current research looks at the valorisation of these waste and wastewater sources through anaerobic digestion, composting and/or nutrient recovery.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.959
Threshold uncertainty score1.000

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 head0.028
GPT teacher head0.265
Teacher spread0.238 · 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.

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
Published2021
Admission routes2
Has abstractyes

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