Tracking U.S. Grain, Oilseed and Related Product Exports in Mexico (Summary)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Texas A&M AgriLife Research and Texas A&M Transportation Institute scientists found that rail continues to be the most important mode of transport for U.S. grains, oilseeds, and products entering Mexico, followed by seaports and trucks. Nearly all Mexican land ports of entry are connected with a U.S. railroad, except for Nuevo Progreso, which does not have rail access (Fig. 1). Increased rail efficiency caused by larger trains and gauge uniformity facilitates North America Railroads (Canada, United States, and Mexico) integration. Once inside Mexico, the majority of the U.S. exports were shipped by rail within Mexico to their final destination (Fig. 2). Two major Mexican rail companies: Ferromex/Ferrosur and Kansas City Southern de Mexico handled U.S. grains, oilseeds, and related products inside Mexico. Jalisco is the largest single destination for rail shipments, followed by Queretaro, and the Estado de Mexico. The largest rail origin-destination pairs, with at least a million metric tons, include Nuevo Laredo-Queretaro, Piedras Negras-Jalisco, Veracruz-Puebla, Nuevo Laredo-Nuevo Leon, Nuevo Laredo-Estado de Mexico, and Ciudad Juárez-Jalisco.
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.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it