Weekly Outlook: Corn Prices Fade as Supplies Expected to Remain in Surplus
Bibliographic record
Abstract
A slightly tighter supply and demand balance for the 2015-16 corn marketing year could be generated by a smaller carryover of old crop corn than currently projected. Based on the current pace of ethanol production, for example, the use of corn for ethanol production during the current marketing year (ending August 31) could be about 10 million bushels more than the current USDA projection of 5.2 billion bushels. Similarly, exports could be slightly larger than the projection of 1.85 billion bushels if Census Bureau export estimates for June, July, and August exceed the USDA export inspection estimates as was the case in the first nine months of the marketing year. However, for carryover stocks to be lower than the current projection of 1.79 billion bushels by enough to meaningfully alter the 2015-16 supply and demand balance would require larger than expected feed and residual use of corn during the final quarter of the marketing year. The USDA’s projection of 5.3 billion bushels of feed and residual use for the year implies fourth quarter use of 522 million bushels. That is 111 million bushels more than use of a year ago and the largest fourth quarter use since 2009. Use is expected to exceed that of a year ago due to an increase in pork and broiler production and small increases in the number of dairy cows and the number of beef cattle on feed. The number of layers has been sharply reduced due to bird flu. Fourth quarter feed and residual use will be revealed with the estimate of September 1 stocks of old crop corn to be released on September 30 and a surprise is always possible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.034 |
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".