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Record W4382600598 · doi:10.1038/s41598-023-37110-3

Impact of sea level rise on the Mediterranean Lithophyllum byssoides rims

2023· article· en· W4382600598 on OpenAlexaff
Aurélie Blanfuné, Charles‐François Boudouresque, Marc Verlaque, Antoine J. P. Minne, Fanny Noisette, Thierry Thibaut

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsEcosystemMediterranean climateMediterranean seaSea levelGeographyMarine ecosystemOceanographyEcologyPhysical geographyBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

The calcified red macroalga Lithophyllum byssoides, a very common midlittoral species in the western Mediterranean Sea, is a significant ecosystem engineer capable, under exposed and dim light conditions, of building wide and solid endemic bioconstructions near the mean sea level: the L. byssoides rims or 'trottoirs à L. byssoides'. Although the growth of the species is relatively rapid for a calcified alga, the construction of a large rim requires several centuries of near stable or slowly rising sea level. As the time scale of their formation is measured in centuries, L. byssoides bioconstructions constitute valuable and sensitive sea level markers. The health status of L. byssoides rims has been studied at two sites located far apart from each other (Marseille and Corsica), both in areas heavily impacted by humans and in areas with little impact (MPAs and unprotected areas). A health index is proposed: Lithophylum byssoides Rims Health Index. The main and inevitable threat is the rise in the sea level. This ecosystem would be the first case worldwide of marine ecosystem collapse resulting, indirectly, from man-induced global change.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.051
GPT teacher head0.261
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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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