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Record W7024715913

Studies on different liquid manure injection tools under laboratory (soil bin) and grassland conditions

2000· other· en· W7024715913 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2000
Typeother
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsManureLoamBinSoil waterLiquid manureGrasslandSoil classification
DOInot available

Abstract

fetched live from OpenAlex

In this study, five different existing liquid manure injection tools (three sweep-types and two disc-types) were evaluated both in the soil bin and at three prairies with heavy clay, coarse sandy loam with stone, and fine sand soil. In the soil bin, the effects of injection depths and tool forward speeds on soil cutting forces and soil disturbance were investigated. While in the field studies, the effects of injection depths and manure application rates on soil disturbances, odor and ammonia concentration, and agronomic response by crop damage and yield were studied. In the soil bin conditions, among the sweeps, sweep A injection tool required the lowest draft force due to its smallest cutting width and rake angle. On the average, sweep B and sweep C required 12 and 97% more draft force than sweep A sweep due to their wider cutting width. In the field study, highest soil disturbance occurred in clay soil due to its wet soil condition. No significant differences in odour concentration were observed between two selected treatments. Similarly, no ammonia concentration was detected from the surface except for higher application rate (112 m 3/ha) combined with shallow injection depth (80 mm) in clay soil. (Abstract shortened by UMI.)

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.555
Threshold uncertainty score0.981

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 head0.004
GPT teacher head0.154
Teacher spread0.150 · 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 designNot applicable
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
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicSoil Mechanics and Vehicle DynamicsFrench-language works237,207