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Record W6959678023 · doi:10.1139/cjas2013-089

Whole-farm budgets of phosphorus and potassium on dairy farms in Manitoba

2014· article· en· W6959678023 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsManurePhosphorusPotassiumManure managementNutrient

Abstract

fetched live from OpenAlex

Plaizier, J. C., Legesse, G., Ominski, K. H. and Flaten, D. 2014. Whole-farm budgets of phosphorus and potassium on dairy farms in Manitoba. Can. J. Anim. Sci. 94: 119-128. Whole-farm budgets of phosphorus (P) and potassium (K) were determined on 10 dairy farms in Manitoba between October 2010 and October 2011. These budgets were determined as the difference between total exports, including milk, animals, feed, and manure, and total imports, including feed, manure, animals, and inorganic fertilizer, for each farm. Farms differed in their feeding and manure management strategies. Two farms imported all their feed and exported all their manure. Other farms produced some of their feed and spread most of their manure on their farm. Whole-farm P and K budgets varied from -0.42 to 3.35 and from -1.31 to 11.27 g kg-1 milk sold among farms, respectively. Efficiencies of P and K utilization were calculated as the exports as a percentage of imports. The P efficiency averaged 48%, and ranged from 22.1 to 109% among farms. The K efficiency averaged 37%, and ranged from 10 to 98% among farms. In the fall of 2010 and 2011, 94 and 98%, of fields sampled had soil test P concentrations lower than the concentration above which further accumulation of P would be regulated (60 ppm). Of the farms that spread their own manure, the highest P and K efficiency were on a farm that exported a proportion of the produced forages and did not import any inorganic fertilizer. The lowest P and K efficiencies were on a farm that imported concentrate feeds, bedding straw and most forages, and had the smallest land base per milking cow to spread manure. Variations in P and K efficiencies demonstrate opportunities to enhance these efficiencies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.372

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 head0.174
GPT teacher head0.203
Teacher spread0.029 · 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
Published2014
Admission routes1
Has abstractyes

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