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Record W1184693980 · doi:10.1177/0959683615596823

Holocene climate history of the Nunatsiavut (northern Labrador, Canada) established from pollen and dinoflagellate cyst assemblages covering the past 7000 years

2015· article· en· W1184693980 on OpenAlexafffundabout
Thomas Richerol, Bianca Fréchette, André Rochon, Reinhard Pienitz

Bibliographic record

VenueThe Holocene · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à MontréalUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of California, IrvineArcticNetUniversité Laval
KeywordsFjordHoloceneOceanographyGeologyDinoflagellateDeglaciationArcticClimate changePhysical geographyPollenGeographyEcology

Abstract

fetched live from OpenAlex

This study documents the past ~7000 years of Holocene climatic history for Labrador and Nunatsiavut, using a sedimentary sequence of more than 8 m retrieved in Nachvak fjord, one of the northernmost fjords of Nunatsiavut. Using a multi-proxy approach combining a solid Accelerator Mass Spectrometry (AMS)- 14 C chronology and the fossil assemblages of pollen grains and dinoflagellate cysts (dinocysts), we were able to compare terrestrial and marine records in an effort to obtain a better understanding of the mid- to late-Holocene climate history of the Nunatsiavut. Records begin at the end of the deglaciation and showed a general delay in the sequence of climate events which followed, both in terrestrial and marine realms. The presence of Pentapharsodinium dalei in great abundance in Nachvak Fjord revealed a strong influence of the North Atlantic Ocean and the Labrador Sea until ~3000 yr BP. Afterward, its rather fast disappearance marked the increased influence of Arctic waters. The last 1000 years show climate stability in the region over the marine realm and a cooling trend over terrestrial landscapes.

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 score0.014
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.200
Teacher spread0.182 · 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

Citations16
Published2015
Admission routes3
Has abstractyes

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