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Record W3200813230 · doi:10.1038/s41598-021-98428-4

Coastal subsidence increases vulnerability to sea level rise over twenty first century in Cartagena, Caribbean Colombia

2021· article· en· W3200813230 on OpenAlexfundno aff
Juan D. Restrepo, Héctor Mora‐Páez, Freddy Díaz Díaz, Marin Govorčin, Shimon Wdowinski, Leidy Giraldo-Londoño, Marko Tošić, I. Peréz Fernandéz, Juan F. Paniagua‐Arroyave, José Duque-Trujillo

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersInternational Development Research CentreUniversidad EAFIT
KeywordsSubsidenceInterferometric synthetic aperture radarTide gaugeSea levelGeologyPhysical geographyOceanographyClimatologyEnvironmental scienceSynthetic aperture radarGeographyRemote sensingGeomorphology

Abstract

fetched live from OpenAlex

Cartagena is subsiding at a higher rate compared to that of global climate-driven sea level rise. We investigate the relative sea level rise (RSLR) and the influence of vertical land movements in Cartagena through the integration of different datasets, including tide gauge records, GPS geodetic subsidence data, and Interferometric Synthetic Aperture Radar (InSAR) observations of vertical motions. Results reveal a long-term rate (> 60 years) of RSLR of 5.98 ± 0.01 mm/yr. The last two decades exhibited an even greater rate of RSLR of 7.02 ± 0.06 mm/yr. GPS subsidence rates range between - 5.71 ± 2.18 and - 2.85 ± 0.84 mm/yr. InSAR data for the 2014-2020 period show cumulative subsidence rates of up to 72.3 mm. We find that geologically induced vertical motions represent 41% of the observed changes in RSLR and that subsidence poses a major threat to Cartagena's preservation. The geodetic subsidence rates found would imply a further additional RSLR of 83 mm by 2050 and 225 mm by 2100. The Colombian government should plan for the future and serve as an example to similar cities across the Caribbean.

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)0.001
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 score0.554
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.240
Teacher spread0.211 · 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

Citations40
Published2021
Admission routes1
Has abstractyes

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