MétaCan
Menu
Back to cohort
Record W2902071571 · doi:10.2478/ntpe-2018-0057

Assessment of Selected On-Board Ballast Water Treatment Systems in Terms of Technical and Operational Parameters

2018· article· en· W2902071571 on OpenAlexfundno aff
Marcin Szczepanek, C. Behrendt

Bibliographic record

VenueNew Trends in Production Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsnot available
FundersIndependent Electricity System OperatorUniwersytet Szczeciński
KeywordsBallastConventionProcess (computing)Selection (genetic algorithm)Set (abstract data type)Relation (database)Computer scienceRisk analysis (engineering)Environmental scienceOperations researchEnvironmental resource managementEngineeringBusinessLawPolitical scienceElectrical engineering

Abstract

fetched live from OpenAlex

Abstract The BWM Convention (Ballast Water Management Convention) will enter into force on 8 September 2017. This document is a response to a very significant problem such as sea water pollution. Due to the Convention, a huge number of companies will be forced to analyze the matter and implement the required provisions. They shall also assess the technologies applied and the fixed systems for ballast water treatment as well as set the requirements in relation to the selection and installation of same at ships. The paper presents the currently applicable regulations and the review of the technologies used for ballast water treatment. There are 5 ballast water treatment systems described herein that are offered by the top producers. The paper includes also the technical and operational parameters of the systems in question. The analysis shall allow for an assessment that may be valuable during the selection process.

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)0.002
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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.240
Teacher spread0.228 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueNew Trends in Production EngineeringSame topicMarine Ecology and Invasive SpeciesFrench-language works237,207