MétaCan
Menu
Back to cohort
Record W2890396295 · doi:10.1139/as-2018-0007

Origin of the southernmost Arctic tundra of continental North America

2018· article· en· W2890396295 on OpenAlexaffvenue
Serge Payette, Vanessa Pilon, Mathieu Frégeau

Bibliographic record

VenueArctic Science · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité LavalCenter for Northern Studies
Fundersnot available
KeywordsTundraBayArcticTaigaBorealPeninsulaTransectVegetation (pathology)OceanographyPhysical geographyGeologyArctic ecologyGeographyArchaeologyPaleontologyForestry

Abstract

fetched live from OpenAlex

The Arctic tundra extends beyond the treeline north of 58°N in eastern North America and north of 66°N in western North America and Eurasia. A marked exception to this distribution is the azonal tundra situated as far south as 54°30′–45′N, in the Pointe-Louis-XIV area (JABA), along the fast-rising coasts of James Bay–Hudson Bay. The unusual position of JABA calls into question the influence of climate as the main causal factor for its existence. Macrocharcoal remains extracted from tundra and forest soils were used along a 105 km transect to date the onset of the boreal environment based on past occurrence of conifer fires. Assuming crustal uplift 1.3 m 100 year −1 and 2.4 m 100 year −1 over and before the last 1000 years, and after correcting site elevation at the time the oldest conifer fires occurred, trees established along the coast before 4000 cal. BP. Given charcoal distribution suggesting boreal vegetation in sites ≤13 m a.s.l., JABA was created after 4000 cal. BP when the flat, elongated peninsula emerged above marine waters. It is concluded that JABA origin was most likely caused by the synergistic impact of geophysical factors, isostatic uplift and topography, on a coastal environment already influenced by cold, wind-exposed conditions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.008
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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.

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

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueArctic ScienceSame topicGeology and Paleoclimatology ResearchFrench-language works237,207