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Record W4388902409 · doi:10.5772/intechopen.113390

Vulnerability and Sea Level Rise in the Coastal Tourism City of Playa del Carmen, Quintana Roo, Mexico

2023· book-chapter· en· W4388902409 on OpenAlexaboutno aff
Jennifer Denisse Ruiz-Ramírez

Bibliographic record

VenueEnvironmental sciences · 2023
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyTourismMangroveUrbanizationRivieraWetlandMexico cityEnvironmental protectionForestryFisheryArchaeologyEcologyHumanities

Abstract

fetched live from OpenAlex

The coastal tourism city of Playa del Carmen is located in the heart of the Mexican Caribbean’s Riviera Maya. This attractive sun and beach destination has the largest number of hotel rooms in the country (i.e. 10,000 more than Cancún), which has made it Mexico’s main magnet for tourists from the United States (US), Canada and Europe. Playa del Carmen is the second biggest city in the state of Quintana Roo and the fastest-growing metropolis in Mexico and Latin America. Rapid urbanisation and tourism development have altered the city’s natural ecosystems, among them mangroves and wetlands. These changes have disturbed the sedimentary dynamics of the coastal dunes and put more pressure on the barrier reef system. The area’s vulnerability was analysed based on flood scenarios of a 1 metre (m), 2 m and 3 m sea level rise to estimate the total property damage in US dollars.

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 score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.213
Teacher spread0.184 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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