Bibliographic record
Abstract
With lower quality and three to four times higher price than those of imported malting barley, the competitiveness of domestic malting barley is decreasing. Although the causes can be found in that the domestic environments are much unfavorable to cultivate the malting barley compared with those of USA or Canada, it is mainly reasoned from poorer developments in variety of high quality malting barley as well as in cultivation technology. For assuring the competitiveness of domestic malting barley, therefore, not only the development of high quality malting barley suitable to the climatic environment of this country but also the political supports of the government are required. Also, in addition to the breeding of the good quality malting barley haying higher germinative energy, and heavier and larger kernels of good plumpness as well as lower protein content, the modification of quality inspection standards from the system relying only on the visual characteristics such as kernel size distribution rate, shrimped kernel rate, foreign materials and so on, to such system as those of developed countries haying quality criteria such as protein content for inspection is absolutely required for the quality improvement of domestic malting barley.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.061 | 0.024 |
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".