Bibliographic record
Abstract
The influence of soil pH on yields and grade-out due to tuber damage by common scab (Streptomyces scabies) was evaluated over multiple cropping seasons for potato (Solanum tuberosum) grown on land heavily infested with S. scabies. Soils with a native pH of 8.0 were adjusted to pH 7.0 to 9.0 using elemental sulfur as an acidulant and calcitic lime as the liming agent. There was little change in total tuber yields over this pH range, but the incidence and severity of scab lesions declined as the pH increased above 8.5. Marketable yields after grade-out to scab were highest at pH 9.0. This study demonstrates that in alkaline soils losses due to potato common scab may be managed by adjusting the soil pH to a point unfavorable to the scab organism. The economics of this type of pH change and its impact on subsequent crops need to be considered. Key words: Common scab, Streptomyces scabies, Solanum tuberosum, liming
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) | 0.000 | 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) | 0.001 | 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 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".