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Record W4283383689 · doi:10.1029/2022gl099230

Rapid Growth of Outer Size of Tropical Cyclones: A New Perspective on Their Destructive Potential

2022· article· en· W4283383689 on OpenAlexaff
Yi Li, Youmin Tang, Shuai Wang

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsUniversity of Northern British Columbia
FundersFundamental Research Funds for the Central UniversitiesNational Outstanding Youth Science Fund Project of National Natural Science Foundation of ChinaNational Natural Science Foundation of China
KeywordsTropical cycloneRADIUSGrowth rateEnvironmental scienceAtmospheric sciencesClimatologyMeteorologyPhysicsGeologyMathematicsComputer scienceGeometry

Abstract

fetched live from OpenAlex

Abstract The destructive potential of a tropical cyclone (TC) is primarily determined by its intensity and outer size. Although TC intensification has been researched extensively, the growth rate of its outer size remains obscure. This prompts us to develop the concept of rapid growth of outer size (RG) of TCs. RG is defined as an increase of at least 75 km in the gale‐force wind radius within 24 hr using an objective anomaly detection algorithm. RG is intrinsically linked to the life cycle of the outer size and comprises most of the peak for large TCs (>300 km) in the distribution of lifetime maximum size. Compared with rapid intensification, RG is a more dangerous change in the TC structure, leveling up the destructive potential more rapidly. This is the first attempt to reveal the importance of RG to the outer size climatology, life cycle, and destructive potential of TCs.

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)0.002
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.026
GPT teacher head0.273
Teacher spread0.247 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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