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Record W2020549070 · doi:10.2136/vzj2014.01.0008

Reproducing Field‐Scale Active Layer Thaw in the Laboratory

2014· article· en· W2020549070 on OpenAlexafffund
Aaron A. Mohammed, Robert A. Schincariol, Ranjeet M. Nagare, William L. Quinton

Bibliographic record

VenueVadose Zone Journal · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsWilfrid Laurier UniversityWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostEnvironmental scienceActive layerBoundary layerTemperature gradientAtmospheric sciencesHydrology (agriculture)GeologyLayer (electronics)Geotechnical engineeringMeteorologyMechanicsMaterials scienceGeography

Abstract

fetched live from OpenAlex

A method to simulate freeze–thaw and permafrost conditions on a large peat‐soil column, housed in a biome, was developed. The design limits ambient temperature interference and maintains one‐dimensional freezing and thawing. An air circulation system, in a cavity surrounding the active layer, allows manipulation of the lateral temperature boundary by actively maintaining an air temperature matching the average temperature of the soil column. Replicating realistic thermal boundary conditions enabled field‐scale rates of active‐layer thaw. Radial temperature gradients were small and temperature profiles mimicked those for similar field conditions. The design allows complete control of key hydrologic processes related to heat and water movement in permafrost terrains without scaling requirement; and presents a path forward for the large‐scale experimental study of frozen ground processes. Because subarctic ecosystems are very vulnerable to climate and anthropogenic disturbances, the ability to simulate perturbations to natural systems in the laboratory is particularly important.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.035
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.245
Teacher spread0.218 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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