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Record W2408587571 · doi:10.5194/cp-12-2215-2016

Climate trends in northern Ontario and Québec from borehole temperature profiles

2016· article· en· W2408587571 on OpenAlexafffundabout
Carolyne Pickler, Hugo Beltrami, Jean‐Claude Mareschal

Bibliographic record

VenueClimate of the past · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of CanadaCompute CanadaSt. Francis Xavier University
KeywordsPermafrostBoreholeGeologyBayClimatologyArcticProxy (statistics)Period (music)Snow coverSnowPhysical geographyOceanographyGeomorphologyGeography

Abstract

fetched live from OpenAlex

Abstract. The ground surface temperature histories of the past 500 years were reconstructed at 10 sites containing 18 boreholes in northeastern Canada. The boreholes, between 400 and 800 m deep, are located north of 51° N and west and east of James Bay in northern Ontario and Québec. We find that both sides of James Bay have experienced similar ground surface temperature histories with a warming of 1.51 ± 0.76 K during the period of 1850 to 2000, similar to borehole reconstructions for the southern portion of the Superior Province and in agreement with available proxy data. A cooling period corresponding to the Little Ice Age was found at only one site. Despite permafrost maps locating the sites in a region of discontinuous permafrost, the ground surface temperature histories suggest that the potential for permafrost was minimal to absent over the past 500 years. This could be the result of air surface temperature interpolation used in permafrost models being unsuitable to account for the spatial variability of ground temperatures along with an offset between ground and air surface temperatures due to the snow cover.

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)0.001
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 score0.018
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.018
GPT teacher head0.212
Teacher spread0.194 · 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

Citations5
Published2016
Admission routes3
Has abstractyes

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