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Record W7162620017

Impact of Fertilizer P Source, Rate, and Placement Strategy on Pea Yield and P Uptake Across Variable Topographies in Saskatchewan

2023· other· en· W7162620017 on OpenAlexfundaboutno aff
Blake Weiseth, Jeff Schoenau, Jane Elliott

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersSaskatchewan Wheat Development CommissionSaskatchewan Canola Development CommissionSaskatchewan Pulse GrowersWestern Grains Research Foundation
KeywordsYield (engineering)FertilizerVariable (mathematics)Crop yieldProduction (economics)
DOInot available

Abstract

fetched live from OpenAlex

The plant availability and mobility in soil of a fertilizer phosphorus (P) source is influenced by the solubility of the fertilizer product itself as well as the reaction products formed in soil over time. In 2022, response of pea yield, P uptake and recovery along with soluble reactive P concentrations in snowmelt water were determined for eight fertilizer P sources applied in a broadcast or side-band placement strategy at a low and high (20 vs 40 kg P2O5 ha-1) rates in the second year of a three-year study conducted at three field sites across SK. The field sites represent unique landform complex positions (knoll, mid-slope, and depression) and provide contrasts in soil properties. Soil P availability assessments conducted in the fall of 2021 following the first year of the study indicate variation in plant-availability of residual P among sources. However, differences in 2022 pea grain and straw yields were no t significant among P treatments, explained by pea being an efficient scavenger of soil P and not highly responsive to P fertilizer management.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.041
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.207
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes2
Has abstractyes

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