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Record W4414181794 · doi:10.1029/2024gl113940

Yucatan Hurricane Activity Highlights Common Era Tropical Cyclone Dipole

2025· article· en· W4414181794 on OpenAlexaff
Richard M. Sullivan, Peter J. van Hengstum, Elizabeth Wallace, Sloan Coats, Jeffrey P. Donnelly, Robert Korty, Shawna N. Little, Luis M. Mejía‐Ortíz, Eduard G. Reinhardt, Courtney Schumacher, Anne E. Tamalavage, Tyler S. Winkler

Bibliographic record

VenueGeophysical Research Letters · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsMcMaster University
FundersUniversity of Texas at AustinGeological Society of AmericaNational Centers for Environmental InformationNational Science Foundation
KeywordsIntertropical Convergence ZoneTropical cycloneYucatan peninsulaAtlantic hurricaneLatitudeProxy (statistics)Northern HemisphereClimate change

Abstract

fetched live from OpenAlex

Abstract Tropical cyclone (TC) impacts along the western Atlantic and Caribbean margin are not spatially uniform. Proxy based reconstructions of Common Era TC activity highlight this non‐uniform distribution at centennial‐millennial timescales. However, the sparse geographic scope of these reconstructions impedes our assessment of TC landfalls across broader spatial domains. This work presents a compilation of new and existing TC reconstructions from the Yucatan Peninsula for comparison with a contemporaneous compilation from New England, showing that these regions occupy distal nodes of a low‐frequency TC dipole. Increased Yucatan (New England) storminess is closely linked to intervals of Northern Hemisphere warming (cooling) and the expansion (contraction) of the Intertropical Convergence Zone, suggesting that secular shifts in the mean climate state mediate dipole orientation.

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 score0.077
Threshold uncertainty score0.154

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.310
Teacher spread0.285 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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