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Record W2010474598 · doi:10.1657/1938-4246-46.1.114

The Fate of Hudson Bay Lowlands Palsas in a Changing Climate

2014· article· en· W2010474598 on OpenAlexaffabout
Andrew Tam, William A. Gough, Sławomir Kowal, Changwei Xie

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsBayPhysical geographyEnvironmental scienceClimate changeGeographyClimatologyGeologyArchaeologyOceanography

Abstract

fetched live from OpenAlex

Abstract The climatological conditions for the presence of palsas in the Hudson Bay Lowlands (HBL) in Ontario, Canada, are examined using data from four climate stations: Big Trout Lake, Lansdowne House, Peawanuck, and Fort Severn. These stations sandwich the existing region where palsas occur. The criteria for the formation and occurrence of palsas that were taken from the literature on Fennoscandian and neighboring Québec palsas were applied to the HBL. Thermal thresholds set at -2 °C and 0 °C mean annual air temperature, and number of days below -10 °C per year were met for the two more northerly locations; the two southerly locations were on the edge of the thresholds. Climate projections from two models under two emission scenarios for the 2020s, 2050s, and 2080s indicated that by the 2080s all four locations would fail the -2 °C threshold for palsa formation but at three locations the 0 °C threshold for palsa presence was met for some projection scenarios. Over the next century, it is likely that the climate conditions will continue to be capable of supporting existing palsas; however, by the end of the century the threshold criteria for new palsa formation will not be met for most of the HBL.

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)0.004
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 score0.041
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.054
GPT teacher head0.315
Teacher spread0.261 · 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

Citations14
Published2014
Admission routes2
Has abstractyes

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