Mexico Transport Cost Indicator Report, September 2022
Bibliographic record
Abstract
What happened?Transportation Costs Varied, But Landed Costs of Grain to Mexico Rose in Second Quarter 2022 Mexico is a major importer of U.S. grain (Grain Transportation Report (GTR) August 25, 2022), tables 13, 14, and 15.Low transportation and landed costs for U.S.-Mexico routes are vital to the competitiveness of U.S. grain (corn, soybeans, and wheat) in Mexico and globally.U.S. grain is transported to Mexico either by cross-border land movements or by sea movements to Mexican ports for inland distribution.This article examines the costs of transporting U.S. grain to Mexico over land to Guadalajara (land routes) and by sea to Veracruz (water routes), tracking changes over time (table 1). Quarter-to-quarter transportation costs.From first quarter 2022 to second quarter 2022 (quarter to quarter), total transportation costs decreased for corn and soybeans shipped through the water routes, but increased for waterborne wheat.Total transportation costs increased for U.S. corn, soybeans, and wheat through the land routes.Falling water-route shipping costs for corn and soybeans mainly reflected lower barge rates. 1 Land-route shipping costs increased with rising truck and rail rates (public tariff, plus fuel surcharge).Truck rates rose partly because of a quarter-to-quarter rise in diesel fuel prices (GTR, fig.13, August 25, 2022).Rail rates rose in response to the increase in fuel surcharges amid higher fuel prices.Reflecting extreme weather and fears of economic downturn, soft demand for barges led to falling barge rates.(GTR, July 28, 2022).Year-to-year transportation costs.From second quarter 2021 to second quarter 2022 (year to year), total costs of shipping all grain to Mexico by the water routes rose because of higher truck, barge, and ocean freight rates.A rise in total costs of shipping all grain to Mexico by the land routes reflected higher truck and rail rates.Quarter-to-quarter landed costs.Quarter to quarter, landed costs rose for all grain shipped via the water and land routes.For seaborne corn and soybeans, higher landed costs reflected rising farm values.For seaborne wheat and all grain shipped through the land routes, landed costs rose because of increases in both transportation costs and 1 Water routes typically involve truck transportation to barge to oceangoing vessel, or truck to rail to oceangoing vessel.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.016 |
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".