Bibliographic record
Abstract
Fruit from black, red and white currants, and gooseberries ( Ribes L.) were grown commercially in North America at the beginning of the 20 th Century. However, when white pine blister rust (WPBR) ( Cronartium ribicola J. C. Fisch.) was introduced into the new world, their cultivation was discontinued. About 825,000 t (908,000 tons) of Ribes fruit are produced worldwide, almost entirely in Europe. The fruit is high in vitamin C, and is used to produce juice, and many other products. Now a wide range of imported Ribes products is available particularly in Canada, and the pick-your-own (PYO) market is increasing. Two diseases, powdery mildew [ Spaerotheca mors-uvae (Schwein.) Berk. & Curt.] and WPBR, are the major problems encountered by growers. Fortunately, many new cultivars are resistant to these two diseases. Commercial acreage of Ribes in North America is located where the growing day degrees above 5 °C (41 °F), and the annual chilling hours are at least 1200. Initially, the Ribes industry will develop as PYO and for farm markets. But for a large industry to develop, juice products will needed. Our costs of production figures indicate that about 850 Canadian dollars ($CDN) per 1.0 t (1.1 tons) of fruit will be required to break even.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".