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Record W4391406285 · doi:10.18174/646845

The cost of degradation of the Dutch North Sea environment - update 2024 : a study into the cost of avoiding degradation and the applicability of the Ecosystem Services approach

2024· report· en· W4391406285 on OpenAlexaff
W.J. Strietman, Felicity Roos, O.M.C. van der Valk, Stijn Reinhard

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsImpact
Fundersnot available
KeywordsDegradation (telecommunications)Environmental scienceEcosystemEnvironmental degradationEcosystem servicesEnvironmental resource managementComputer scienceEcologyTelecommunicationsBiology

Abstract

fetched live from OpenAlex

This report provides an insight into the cost of degradation of the marine environment of the Dutch part of the North Sea by calculating the annual current (2022) costs of measures that avoid or minimise degradation. In addition to this, insight is provided into the potential applicability of the ecosystem services approach to calculate ecosystem benefits gained when Good Environmental Status is reached, in comparison to a Business-as-Usual scenario. The total costs of measures that avoid degradation of the Dutch North Sea environment have been calculated to be in the range of approximately at least €7.19-2.02bn in 2022. In terms of the applicability of the Ecosystem Services Approach methodology, it is concluded that the methodology and empirical application are not mature enough yet and that the data needed are too limited to be applied within the context of the Marine Strategy Framework Directive.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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