Estimated Impacts of Mexican Transportation Infrastructure Improvements on the U.S. Meat Complex
Bibliographic record
Abstract
What is the Issue?Mexico is one of the top four export markets for U.S. beef, the others being Japan, South Korea, and Canada.U.S. beef, pork, poultry meat, and edible offal exports to Mexico averaged 3.48 billion pounds per year from 2011 to 2015, valued at $3.01 billion.The United States also imports animals and meat from Mexico, mostly beef and cattle.From 2011to 2015, U.S. imports of live cattle from Mexico averaged 1.2 million head, valued at $692.6 million.These exports and imports cross into and out of Mexico almost entirely over land borders and mostly via truck.Texas is the most important State for U.S. meat and live cattle exports to Mexico.Texas and California are most important for meat imports to the United States from Mexico.New Mexico and Arizona are most important for live cattle imports to the United States from Mexico.As U.S.-Mexico trade in the meat and live animal complex has grown, both countries have significantly improved their infrastructure.Texas AgriLife and Texas A&M University research scientists analyzed the impact of recent Mexican infrastructural improvements on the U.S.-Mexico meat and livestock trade.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".