Development of a <i>Brassica</i> seed cDNA microarray
Bibliographic record
Abstract
Brassica species represent several important crops including canola (Brassica napus). Understanding of genetic elements that contribute to seed-associated functions will impact future improvements in the canola crop. Brassica species share a very close taxonomic and molecular relationship with Arabidopsis thaliana. However, there are several subtle but distinct seed-associated agronomic characteristics that differ among the oil seed crop species. To address these, we have generated 67,535 ESTs predominately from Brassica seeds, analyzed these sequences, and identified 10,642 unigenes for the preparation of a targeted seed cDNA array. A set of 10,642 PCR primer pairs was designed and corresponding amplicons were produced for spotting, along with relevant controls. Critical quality control tests produced satisfactory results for use of this microarray in biological experiments. The microarray was also tested with specific RNA targets from embryos, germinating seeds, and leaf tissues. The hybridizations, signal intensities, and overall quality of these slides were consistent and reproducible. Additionally, there are 429 ESTs represented on the array that show no homology with any A. thaliana annotated gene or any gene in the Brassica genome databases or other plant databases; however, all of these probes hybridized to B. napus transcripts, indicating that the array also will be useful in defining expression patterns for genes so far unique to Brassica species.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".