<i>Pectobacterium</i> spp. Associated with Bacterial Stem Rot Syndrome of Potato in Canada
Bibliographic record
Abstract
Pectobacterium atrosepticum, P. carotovorum subsp. brasiliensis, P. carotovorum subsp. carotovorum, and P. wasabiae were detected in potato stems with blackleg symptoms using species- and subspecies-specific polymerase chain reaction (PCR). The tests included a new assay for P. wasabiae based on the phytase gene sequence. Identification of isolates from diseased stems by biochemical or physiological characterization, PCR, and multi-locus sequence typing (MLST) largely confirmed the PCR detection of Pectobacterium spp. in stem samples. P. atrosepticum was most commonly present but was the sole Pectobacterium sp. detected in only 52% of the diseased stems. P. wasabiae was most frequently present in combination with P. atrosepticum and was the sole Pectobacterium sp. detected in 13% of diseased stems. Pathogenicity of P. wasabiae on potato and its capacity to cause blackleg disease were demonstrated by stem inoculation and its isolation as the sole Pectobacterium sp. from field-grown diseased plants produced from inoculated seed tubers. Incidence of P. carotovorum subsp. brasiliensis was low in diseased stems, and the ability of Canadian strains to cause blackleg in plants grown from inoculated tubers was not confirmed. Canadian isolates of P. carotovorum subsp. brasiliensis differed from Brazilian isolates in diagnostic biochemical tests but conformed to the subspecies in PCR specificity and typing by MLST.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".