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Record W2586179324 · doi:10.1038/srep41878

Multiple tropical Andean glaciations during a period of late Pliocene warmth

2017· article· en· W2586179324 on OpenAlexafffund
Nicholas J. Roberts, René W. Barendregt, John J. Clague

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of LethbridgeSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlacial periodGeologyGlacierPleistocenePaleontologyDeglaciationMarine isotope stagePeriod (music)InterglacialQuaternaryPhysical geographyGeography

Abstract

fetched live from OpenAlex

concentrations above pre-industrial levels. Knowledge of glaciation during this period is restricted to globally or regionally averaged records from marine sediments and to sparse terrestrial glacial deposits in mid-to-high latitudes. Here we expand the Pliocene glacial record to the tropics by reporting recurrent large-scale glaciation in the Bolivian Andes based on stratigraphic and paleomagnetic analysis of a 95-m sequence of glacial sediments underlying the 2.74-Ma Chijini Tuff. Paleosols and polarity reversals separate eight glacial diamictons, which we link to cold periods in the benthic oxygen isotope record. The glaciations appear to coincide with the earliest glacial activity at high northern latitudes and with events in Antarctica, including the strong M2 cold peak and terminal Pliocene climate deterioration. This concordance suggests inter-hemispheric climate linkages during the late Pliocene and requires that the Central Andes were at least as high in the late Pliocene as today. Our record fills a critical gap in knowledge of Earth systems during the globally warm mid-Piacenzian and suggests a possible driver of faunal migration preceding the large-scale biotic interchange in the Americas during the earliest Pleistocene.

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 score0.019
Threshold uncertainty score0.038

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.256
Teacher spread0.234 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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