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Record W2130656353 · doi:10.1029/2000gl008483

Energy balance at the Earth's surface: Heat flux history in eastern Canada

2000· article· en· W2130656353 on OpenAlexafffundabout
Hugo Beltrami, Jingfeng Wang, Rafael L. Bras

Bibliographic record

VenueGeophysical Research Letters · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeat fluxFlux (metallurgy)Geothermal gradientEnergy balanceEnvironmental scienceGeothermal energyGeologyGeothermal heatingGeophysicsRange (aeronautics)Atmospheric sciencesClimatologyHeat transferPhysicsMaterials scienceMechanicsThermodynamics

Abstract

fetched live from OpenAlex

The heat exchange at the air/ground interface is determined by many complex processes making the energy balance at the earth's surface extremely difficult to quantify and model. A new methodology allows heat flux at the Earth's surface to be estimated using ground surface temperature history reconstructed from geothermal data. We found that over a large region in eastern and central Canada, the average heat flux into the ground during the last 1000 years was on the order of 2.8 mWm−2. Our results suggest that significant change in the ground heat flux occurred in the last two centuries. The 200 years averaged heat flux since 1765 is 17.0 mWm−2, while the average heat flux over the latest 100 years is 74.0 mWm−2. The sensitivity of the subsurface to very small energy imbalances makes these type of data and analysis useful complements to the paleoclimatic record; they also provide constrains for general circulation model land‐surface parameterization over a wide range of spatial‐temporal scales.

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 score0.030
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.012
GPT teacher head0.215
Teacher spread0.204 · 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

Citations56
Published2000
Admission routes3
Has abstractyes

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