Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".