An Oligonucleotide Array for the Identification and Differentiation of Bacteria Pathogenic on Potato
Bibliographic record
Abstract
ABSTRACT Oligonucleotides, 16 to 24 bases long, were selected from the 3' end of the 16S gene and the 16S-23S intergenic spacer regions of bacteria pathogenic on potato, including Clavibacter michiganensis subsp. sepedonicus, Ralstonia solanacearum, and the pectolytic erwinias, including Erwinia carotovora subsp. atroseptica and carotovora and E. chrysanthemi. Oligonucleotides were designed and formatted into an array by pin spotting on nylon membranes. Genomic DNA from bacterial cultures was amplified by polymerase chain reaction using conserved ribosomal primers and labeled simultaneously with digoxigenin-dUTP. Hybridization of amplicons to the array and subsequent serological detection of digoxigenin label revealed different hybridization patterns that were distinct for each species and subspecies tested. Hybridization of amplicons generally was restricted to appropriate homologous oligonucleotides and cross-hybridization with heterologous oligonucleotides was rare. Hybridization patterns were recorded as separate gray values for each hybridized spot and revealed a consistent pattern for multiple strains of each species or subspecies isolated from diverse geographical regions. In preliminary tests, bacteria could be correctly identified and detected by hybridizing to the array amplicons from mixed cultures and inoculated potato tissue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".