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Record W4200250447 · doi:10.1029/2021gl094036

Coral Oxygen Isotopic Records Capture the 2015/2016 El Niño Event in the Central Equatorial Pacific

2021· article· en· W4200250447 on OpenAlexaff
Gemma K. O’Connor, K. M. Cobb, Hussein R. Sayani, Alyssa R. Atwood, Pamela R. Grothe, Samantha Stevenson, Julia K. Baum, Tianran Chen, Danielle C. Claar, N. T. Hitt, Jean Lynch‐Stieglitz, Richard A. Mortlock, Gavin A. Schmidt, Rachel M. Walter

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of Victoria
FundersGeorgia Institute of TechnologyNational Science Foundation
KeywordsCoralOceanographySeawaterSea surface temperatureSalinityTemperature recordGeologyIsotopes of oxygenδ18OClimatologyPacific oceanEnvironmental scienceStable isotope ratioClimate change

Abstract

fetched live from OpenAlex

Abstract Coral oxygen isotopes (δ18O) from the central equatorial Pacific provide monthly resolved records of El Niño‐Southern Oscillation activity over past centuries to millennia. However, calibration studies using in situ data to assess the relative contributions of warming and freshening to coral δ18O records are exceedingly rare. Furthermore, the fidelity of coral δ18O records under the most severe thermal stress events is difficult to assess. Here, we present six coral δ18O records and in situ temperature, salinity, and seawater δ18O data from Kiritimati Island (2°N, 157°W) spanning the very strong 2015/16 El Niño event. Local sea surface temperature (SST) anomalies of +2.4 ± 0.4°C and seawater δ18O anomalies of −0.19 ± 0.02‰ contribute to the observed coral δ18O anomalies of −0.58 ± 0.05‰, consistent with a ∼70% contribution from SST and ∼30% from seawater δ18O. Our results demonstrate that Kiritimati coral δ18O records can provide reliable reconstructions even during the largest class of El Niño events.

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 score0.029
Threshold uncertainty score0.058

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 communication0.0000.000
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 head0.024
GPT teacher head0.296
Teacher spread0.272 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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