Bibliographic record
Abstract
In laboratory and packing house experiments, treatment of potato tubers with steam or organic mercury reduced the incidence of the seed-borne pathogens Erwinia carotovora (Jones) Bergey et al. and Helminthosporium solani (Dur. & Mont.), and the seed- and soil-borne pathogens Streptomyces scabies (Thaxter), Spongospora subterranae (Waller), Fusarium spp., Rhizoctonia solani (Kuhn), and Colletotrichum coccodes (Waller) in tubers. The incidence of pathogens in tubers following these treatments was 1–3% compared with 26–59% in the nontreated controls. Similar results were obtained in a commercial packing house in Israel when stream treatments were applied to tubers using a nozzle system that was fitted to a conveyor belt and attached to a diesel-powered steamer. The presence of seed-borne pathogens in the daughter tubers 120 days postplanting of steam or organic mercury treated tubers was 3–4% compared with 26–31% in the nontreated controls. The treatments were slightly more effective against pathogens that were exclusively seed-borne compared with those that were both seed- and soil-borne. The presence of pathogens that were both seed- and soil-borne in the daughter tubers following these treatments was 4–9% compared with 20–44% in the nontreated control. Neither steam nor organic mercury treatments had any adverse effects on tuber viability and on plant vigor, foliage, or mass, nor on viability or yield of daughter tubers 120 days postplanting in the field, compared with the nontreated control. These results demonstrate that steam treatment can be an efficient method for disinfecting potato tubers, easily applied in packing houses to large volumes.
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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 | 0.000 |
| 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) | 0.002 | 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".