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Record W4311720354 · doi:10.3390/data7120174

Determination of Soil Behavior during Evaporation Using Geotechnical Datasets

2022· article· en· W4311720354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueData · 2022
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSoil waterEvaporationEnvironmental scienceGeotechnical engineeringSoil scienceDistilled waterShrinkageSoil testWater retentionInertHydrology (agriculture)GeologyMaterials scienceChemistryComposite material

Abstract

fetched live from OpenAlex

Evaporation from soils is critical for agricultural water management. This requires a clear understanding of the water retention and soil shrinkage behavior of soils during water escape and due to fertilizers usage. Based on laboratory testing, this paper provides a comprehensive dataset generated for the determination of the geotechnical properties of inert silty sand and active lean clay using distilled water and saline pore fluid under ambient conditions. The tests include fluid-independent general soil properties, fluid-dependent specific soil properties, low-demand evaporation as a baseline, and high-demand evaporation to capture summer.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.245

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)0.0000.000

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 head0.041
GPT teacher head0.276
Teacher spread0.235 · 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