Weekly Outlook: USDA Grain Stocks and Acreage Estimates Supportive for Corn and Soybean Prices
Bibliographic record
Abstract
The estimate of June 1 stocks is most important for corn since it reveals the magnitude of feed and residual use during the previous quarter. This year, however, the soybean stocks estimate is of more interest than usual since both the December 1, 2014 and March 1, 2015 stocks estimates revealed an unusually large residual disappearance in the first half of the year and hinted that the 2014 crop may have been overestimated. The June acreage estimates are always important since they differ from intentions in the March Prospective Plantings report and provide an update of production prospects. The estimates are of extreme interest this year due to the seeming under-statement of total crop acreage in the March intentions report and the delay in soybean planting. That delay, however, also creates more than the usual uncertainty about how final planted and harvested acreage estimates will compare to June intentions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.012 |
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".