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Record W2032448857 · doi:10.1029/2005gl023714

Long‐term tracking of climate change by underground temperatures

2005· article· en· W2032448857 on OpenAlexafffund
Hugo Beltrami, Grant Ferguson, Robert N. Harris

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric SciencesNational Science Foundation
KeywordsBoreholeGeothermal gradientSnowEnvironmental scienceGeologyClimate changeGeothermal energyTerm (time)Energy balanceClimatologyAtmospheric sciencesGeophysicsGeomorphologyPhysics

Abstract

fetched live from OpenAlex

Underground temperatures contain a record of past changes in the energy balance at the Earth's surface, such that borehole temperature data can be used to reconstruct long‐term trends of ground surface temperature (GST) changes. In addition to surface air temperature, however, GST is the response of the ground to other near surface processes that govern the surface energy balance. In order to compare GST histories constructed from geothermal data with surface air temperature (SAT) data, it is necessary to ascertain the relationship between these quantities. Here we jointly interpret four borehole temperature logs within a small area and SAT records from a nearby station. The subsurface temperature anomalies are consistent with the SAT data even in the presence of a variable snow regime, and different surface conditions. Our results indicate that borehole records are robust long‐term paleoclimatological indicators.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.089
GPT teacher head0.333
Teacher spread0.244 · 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

Citations52
Published2005
Admission routes2
Has abstractyes

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