Grain Transportation Report, April 17, 2025
Bibliographic record
Abstract
CN Grain Carloads Reach All-Time Weekly High.According to data from the Surface Transportation Board, Canadian National Railway (CN) achieved an all-time weekly record of 2,384 originated grain carloads on its U.S. network, for the week ending April 5 (Grain Transportation Report (GTR) table 3).For comparison, this amount was 82 percent higher than the previous week and 69 percent higher than the 5-year average for the same week.CN's U.S. network connects export terminals on the U.S. Gulf with inland grain elevatorsprimarily, in Illinois, and to a lesser degree, Iowa and Wisconsin.Running parallel to the Mississippi River, CN's U.S. network substitutes for barge transport, and CN's grain carloads generally peak during periods of barge disruptions (e.g., following the 2022 harvest) or during strong export demand.The surge in CN's grain carloads likely reflected a surge of export demand, anticipating changes in trade relations between the United States and major grain buyers. High Water and Delayed Lock Reopening Slow Barge Traffic.As of April 17, docks on the upper Ohio River have begun to reopen after being closed last week because of high water from severe storms (GTR, April 10, 2025, first highlight).Docks along the lower Ohio River should be able to begin loading by the end of this week.Currently, however, at the Smithland Lock and Dam (in Brookport, IL, on the lower Ohio River) mechanical problems are halting tows to and from the river.The lock is expected to reopen over the weekend.According to the National Oceanic and Atmospheric Administration (NOAA)-in Baton Rouge, LA, flooding is expected to crest on April 26 at 40.5 feet, which is considered major flooding.Since the minor flood stage at Baton Rouge, assist boats have had to help vessels pass under bridges in the area.Daylight restrictions for high water continue around Memphis, TN, and Vicksburg, MS.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.112 | 0.109 |
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".