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Record W2523125759

DUAL-PURPOSE WINTER WHEAT AND STOCKER PRODUCTION By

2013· article· en· W2523125759 on OpenAlexfundno aff
Karen W. Taylor

Bibliographic record

VenueSHAREOK (University of Oklahoma) · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
FundersRoyal Bank of CanadaOklahoma State University
KeywordsProduction (economics)Environmental scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

Scope and Method of Study: The purpose of this study was to research the dual-purpose winter wheat and stocker industry in the Southern Plains. Three research studies were conducted. The first study was performed to determine the value of two monensin supplementation strategies for cattle pastured on fall-winter wheat relative to the value of a free-choice mineral supplement containing no monensin. A second objective was to determine the value of extending the fall-winter wheat pasture grazing season by either one or two weeks. An enterprise budgeting framework was used to simulate returns values and then stochastic efficient with respect to a function (SERF) was performed to find risk efficient production strategies. The second study determined the optimal grazing termination date for dual-purpose winter wheat that maximizes the returns of cattle and wheat production. A second objective was to determine the value of information regarding the occurrence of first hollow stem (FHS). A profit maximization model was used. Price response functions to determine stocker sale prices and a unique plateau function to find wheat yields were found. Econometric analysis was performed to determine the optimal grazing termination date. The third study constructed a dual-purpose winter wheat and stocker production planner. The stocker planner is intended to aid stocker producers determine the optimal purchase stocker weight and gender, the optimal time to terminate fall-winter grazing on wheat intended for grain harvest, and the optimal time to concentrate animals on the proportion of wheat acres to be grazed-out.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.150
Teacher spread0.144 · 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.

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
Published2013
Admission routes1
Has abstractyes

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