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Record W4407187095 · doi:10.1002/vzj2.20396

Insights into freeze–thaw and infiltration in seasonally frozen soils from field observations

2025· article· en· W4407187095 on OpenAlexafffundabout
Ines Sanchez‐Rodriguez, Andrew Ireson, Rosa Brannen, Haley Brauner

Bibliographic record

VenueVadose Zone Journal · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change CanadaGlobal Institute for Water SecurityWater Security AgencyUniversity of Saskatchewan
FundersGlobal Water FuturesUniversity of Saskatchewan
KeywordsInfiltration (HVAC)Soil waterEnvironmental scienceHydrology (agriculture)Soil scienceGeologyGeotechnical engineeringGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract Snowmelt infiltration into frozen soils in seasonally frozen landscapes is a critically important hydrological process, with consequences for agriculture, water resources, and flooding. The partitioning of snowmelt between infiltration and runoff in any given location and in any given year is highly uncertain. While it is intuitive to expect lower infiltration capacities in frozen soils, extensive past field research has shown that infiltration is often the dominant flux over runoff during this process, and this is attributed to infiltration into air‐filled macropores. Despite this understanding, we still lack models that can predict frozen soil infiltration reliably. In this study, we examine detailed field observations from the seasonally frozen Canadian Prairies to determine the controls on soil freeze/thaw, snowmelt partitioning, and groundwater recharge. We show how soil moisture, water table depth, snow water equivalent, and air temperature are all significant and confounding factors that determine soil freezing depth and snowmelt partitioning.

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)0.000
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 score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.030
GPT teacher head0.243
Teacher spread0.213 · 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

Citations11
Published2025
Admission routes3
Has abstractyes

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