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Record W2947537698 · doi:10.1016/j.dib.2019.104078

Dataset on marine ecosystem services supplied by coral reefs, sandy beaches and coastal lagoons in different eutrophication states

2019· article· en· W2947537698 on OpenAlexaff
Charlène Kermagoret, Joachim Claudet, Valérie Derolez, Maggy M. Nugues, Vincent Ouisse, Nolwenn Quillien, Denis Bailly

Bibliographic record

VenueData in Brief · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversité du Québec en Outaouais
FundersAgence Nationale de la Recherche
KeywordsEutrophicationCoral reefEcosystem servicesEcosystemHabitatTrophic levelEnvironmental scienceBiodiversityEcologyRecreationMarine ecosystemResilience of coral reefsFisheryEnvironmental resource managementGeographyNutrientBiology

Abstract

fetched live from OpenAlex

This data article provides indicators of Ecosystem Service (ES) supply for coral reefs, sandy beaches and coastal lagoons in different ecological states regarding eutrophication. 14 ES are considered: food through fisheries; material; molecules; coastal protection; nutrient regulation; pathogen regulation; climate regulation; support of recreational and leisure activities; contribution to a pleasant landscape; contribution to culture and territorial identity; emblematic biodiversity; habitat; trophic networks; recruitment. For each ecosystem 3 to 4 eutrophication states are described. Indicators of ES supply are filled on the basis of a literature review supplemented with expert-knowledge. A semi-quantification of the indicator value is finally provided. Tendencies and trade-offs between ES are analyzed in How does eutrophication impact bundles of ecosystem services in multiple coastal habitats using state-and-transition models [1].

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.993

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 science0.0000.002
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 head0.011
GPT teacher head0.220
Teacher spread0.210 · 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
Published2019
Admission routes1
Has abstractyes

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