Bibliographic record
Abstract
Feeder cattle prices are determined by the interaction of numerous factors. As economic conditions change over time, price differentials associated with feeder cattle weight vary. This study analyzes transactions data on 46,081 pens of feeder cattle over a 10‐year period. Results indicate that fed‐cattle futures prices and corn prices are important determinants of price‐weight relationships for feeder cattle. Time of year, recent feeding margins and sex of feeder cattle have moderate impacts on the price‐weight relationship (i.e., price slides). Coefficients of variation for fed cattle and corn prices have economically unimportant impacts on price relationships. Results of this model can be used to assess feeder cattle price relationships across weights as fed cattle and corn prices vary. Les prix des bovins d'engraissement sont fonction de I'interaction de nombreux facteurs. Au fil des changements des conditions économiques, les écarts de prix associés au poids des bovins varient. Nous étudions les données de transactions réalisées dans une période de 10 ans sur 46 081 parquets de bovins d'engraissement. II ressort de ce travail que les prix è terme des bovins finis et le prix du maïs sont d'importants déterminants des rapports prix‐poids pour ce type d'animaux. L'époque de I'année, les marges d'engraissement récentes et le type sexuel des bovins n'ont que des répercussions modérées sur le rapport prix‐poids (c.‐a‐d. I'écart de prix aux 100 Ib selon lepoids de I'animal). Les coefficients de variation relatifs aux prix des bovins finis et è ceux du maïs sont dénués de toute importance économique pour les rapports de prix. Les résultats du modèle peuvent être utilisés pour évaluer les rapports de prix des bovins d'engraissement selon une échelle de poids en fonction des variations des prix des bovins gras et de ceux du maïs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".