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Record W4417209928 · doi:10.1088/2515-7620/ae2b54

Atlantic Multidecadal Oscillation associated with all-cause mortality in United States

2025· article· en· W4417209928 on OpenAlexafffund
Haris Majeed, Daniyal Zuberi

Bibliographic record

VenueEnvironmental Research Communications · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAtlantic multidecadal oscillationNorth Atlantic oscillationClimate changeMortality rateClimate pattern

Abstract

fetched live from OpenAlex

Abstract A complex mix of factors explains the decline in adult all-cause mortality in the United States over the past century. Throughout the century, advances in social policies, infrastructure, and health care have all played an important contributing role in this decline. Yet the declining trend has oscillated over time, with different patterns also emerging by gender and race/ethnicity. Only limited research thus far has focused on the role of climate factors, especially with respect to large-scale Atlantic Oceanic variability through the Atlantic Multidecadal Oscillation (AMO). This paper presents an analysis of the association of AMO phases with all-cause mortality in the United States over the past century. The findings point to divergent impacts based on gender and race, with males and Black populations experiencing higher ( β Black = 1.21 versus β White = 0.39) all-cause mortality during negative phases of the AMO, indicative of cooler-than-normal North Atlantic sea surface temperatures. These findings suggest the importance and need for further research and analyses to explore the impact of climate patterns on health and mortality outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.233
GPT teacher head0.454
Teacher spread0.221 · 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 teacher head, 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

Citations0
Published2025
Admission routes2
Has abstractyes

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