Weekly Outlook: USDA Grain Stocks and Acreage Estimates Supportive for Corn and Soybean Prices
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
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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