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Record W2888948302

Can the quality of soil structure be maintained following repeated applications of high rates of hog manure

2002· article· en· W2888948302 on OpenAlexaboutno aff
T.B. Zeleke, M.C.J. Grevers, B.C. Si, J.J. Schoenau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
Fundersnot available
KeywordsManureQuality (philosophy)Environmental scienceAgronomySoil structureAgricultural engineeringSoil scienceSoil waterBiologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The long-term impact of repeated applications of high rates of liquid hog manure on the quality of the soil and that of the environment is not well known. For optimal application rates of hog manure, improved knowledge is essential regarding the long-term effect of hog manure applications on salinity, acidity, soil density, aggregation, and soil strength. A field research project was initiated in 1998 to determine the effects of repeated application of high rates of injected swine manure (up to 13,000 g ac-1) on soil quality in Southern Saskatchewan. In the fall 2001, measurements were made on different soil physical and chemical quality indicators in two of the sites with contrasting soil types: a heavy clay textured soil in the Dark Brown Soil Zone and a sandy loam to loam textured soil in the Brown Soil Zone. At the site with heavy clay textured soil, the high rates of liquid hog manure increased sodium absorption ratio (SAR), electrical conductivity (EC), and surface penetration resistance (SPR) and decreased soil pH; whereas, there were no significant changes on the quality of the surface soil at the sandy loam to loam textured soil to date other than a decrease in surface crusting index. Studies are in progress to include additional sites and also additional soil quality indicator parameters through a longer term monitoring program.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
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)0.0000.000

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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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