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Record W2152258617 · doi:10.1029/2006gl028469

Caribbean and Pacific moisture sources on the Isthmus of Panama revealed from stalagmite and surface water <i>δ</i><sup>18</sup>O gradients

2007· article· en· W2152258617 on OpenAlexaff
Matthew S. Lachniet, William P. Patterson, S. Burns, Yemane Asmerom, Victor J. Polyak

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsStalagmiteIntertropical Convergence ZonePanamaMoistureGeologyOceanographySea surface temperaturePacific oceanClimatologyδ18OCaveTropical Eastern PacificGeographyHolocenePrecipitationStable isotope ratioMeteorology

Abstract

fetched live from OpenAlex

We test the hypothesis that the Pacific Ocean contributes moisture to the Intertropical Convergence Zone (ITCZ) over southern Central America, by spatial analysis of surface water δ18O values from Panama and Costa Rica. The δ18O values decrease with distance from the Caribbean Sea to the isthmian divide then gradually increase from the divide toward the Pacific slope, which suggests a contribution of both Caribbean and Pacific sourced moisture to the isthmus. We estimated the Pacific moisture contribution for Pacific slope regions of 22% to 64%. The δ18O values from stalagmites from five cave systems demonstrate decreasing δ18O values with distance from the Caribbean, implicating the Atlantic Basin as a dominant moisture source. Constraining modern moisture sources is important for the interpretation of stable isotopic proxy records of past rainfall, because of the combined influence of Pacific and Atlantic ocean‐atmosphere phenomena on ITCZ rainfall over the Isthmus of Panama.

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)0.001
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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

Citations50
Published2007
Admission routes1
Has abstractyes

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