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Record W2323895933 · doi:10.2136/vzj2012.0075

Effect of Tillage on Soil Water Content and Temperature Under Freeze–Thaw Conditions

2013· article· en· W2323895933 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVadose Zone Journal · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsHealth CanadaUniversity of Guelph
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsTillageWater contentEnvironmental scienceConventional tillageSoil scienceSoil waterHydrology (agriculture)Animal scienceAgronomyGeologyBiologyGeotechnical engineering

Abstract

fetched live from OpenAlex

High resolution (hourly) soil water content and temperature data have been collected for nearly 10 yr within the 0–100 cm depth profiles under no‐till (NT) and conventional fall tillage (CT) practices. The data indicate significant differences between the two tillage practices, especially during winter and early spring freeze\thaw cycles. Results indicate that shallow minimum soil temperatures were lower under CT than NT; however, average winter shallow soil temperatures were very similar between the two treatments. Soil freezing characteristic curves (SFC) measured in situ with soil water content and temperature data were analyzed for differences between treatments as the NT system matured. The SFC shapes for NT evolved over a 7‐yr period as the age of the NT system increased. An intensive freeze–thaw episode showed strong hysteresis in SFC, a phenomenon not analyzed in detail before this study based on data collected in the field.

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 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 score0.358
Threshold uncertainty score0.979

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)0.0220.000

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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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