Determinants of the Choice-Select spread
Bibliographic record
Abstract
The Choice-Select (C-S) spread is the difference between the Choice and Select carcass cut-out values and is an important market indicator for feedlots and producers within the United States. It presents the direct discount for Select grading cattle carcasses. Over the past several decades the Choice-Select spread has generated extensive seasonality, which can cause financial stress on feedlots and cattle producers due to fluctuating prices. The goal of this research is to quantify the determinants of the Choice-Select spread. Results from partial adjustment econometric models suggests the percentage quantity of Choice graded beef (i.e. relative supply of Choice beef) was the most influential determinant for the Choice-Select spread; that is, a 1% increase in quantity resulted (P = 0.058) in a $21-24/cwt decrease in the spread. The estimation also found that $1 change in consumer demand driven wholesale boxed beef prices lead (P < 0.01) to a $0.069-0.072/cwt increase in the spread. The model also identified a statistically significant (P = 0.037) seasonal effect of roughly $0.684-0.80/cwt on the spread during the months of April to August (the grilling season).
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 | 0.006 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".