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Record W4361005977 · doi:10.3390/geosciences13040097

Evolution of Coastal Subarctic Lakes in the Context of Climatic and Geological Changes and Human Occupation (North-Central Labrador, Canada)

2023· article· en· W4361005977 on OpenAlexafffundabout
Camille Latourelle-Vigeant, Reinhard Pienitz, Najat Bhiry

Bibliographic record

VenueGeosciences · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité Laval
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsSubarctic climateBayContext (archaeology)ArchipelagoGeologySedimentVegetation (pathology)OceanographyClimate changePhysical geographyEcosystemEcologyGeographyPaleontology

Abstract

fetched live from OpenAlex

Climate fluctuations and landscape evolution, with their associated impacts on northern coastal ecosystems, likely influenced human populations of Nunatsiavut who have inhabited the region for nearly 7000 years. As part of an interdisciplinary research initiative within the Nain Archipelago on the subarctic coast of Labrador, this project sought to reconstruct the postglacial palaeoclimatic and palaeoenvironmental variability of Dog Island and document its impacts on the evolution of lakes located in the vicinity of significant archaeological sites. To address these questions, we analysed physical, geochemical, and biological indicators preserved in sediment cores of two lakes. Results from Oakes Bay West Lake revealed gradual acidification since ca. 4900 cal. yr BP, coherent with terrestrial vegetation development and/or neoglacial cooling, interrupted by periods of milder climatic conditions (ca. 4900–3640 cal. yr BP and ca. 1520 cal. yr BP—present) that favoured large sediment inputs. Evilik Lake revealed the classic sequence of isolation of the basin in three major phases in response to glacio-isostatic rebound. These complementary results allowed for the development of a local palaeoenvironmental framework that contributes to a better understanding of how landscape evolution and climate have influenced human societies through site availability and proximity to marine resources, and how, in turn, they impacted their immediate environment through activities, such as wood harvesting and its associated effects on nutrients and lake sediment inputs.

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 score0.726
Threshold uncertainty score0.742

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 science0.0000.000
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 head0.023
GPT teacher head0.244
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

Citations1
Published2023
Admission routes3
Has abstractyes

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