Bibliographic record
Abstract
● Washington State ranks #1 in the nation in production of apples. Washington growers produce about 53 % of the apples grown in the United States, and 66 % of those grown for fresh consumption. ● Apple acreage in Washington is estimated at about 192,000; an estimated 10,000 acres are non-bearing. ● Apples are the #1-ranked commodity grown in Washington State. During 1994-1998, production averaged about 117,000,000 bushels (boxes), with an average of 88,000,000 sold as fresh and 29,000,000 processed. ● Farmgate value of Washington apples is estimated at about $950 million yearly, with total value of the packed box and processed product sales nearing $1.5 billion. ● From 28 to 35 percent of the crop is exported yearly, with major markets in the Asian Rim, Canada, Mexico, and South America. ● Cost to produce an acre of apples is about $5800 to $6600. The greatest expense is labor for picking, pruning, and hand fruit thinning. Packing and marketing costs an additional $3,600 per acre of production. ● The average break-even price for a box of apples is about $13.50; in 1998, growers received an average of $10.51.
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.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.292 | 0.186 |
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".