Exact word matches in rice pseudomolecules
Bibliographic record
Abstract
Using pseudomolecules of assembled genomic sequence, we computed the frequencies of 6 to 24 bp oligonucleotide (oligo) "words" across the genome of rice (Oryza sativa L. subsp. japonica). All oligos of 10 or fewer basepairs were repeated at least 12 times in the genome. The percentage of unique (non-repeated) oligos ranged from 0.1% for 12 bp oligos to 76.0% for 24 bp oligos. For three 200 kb regions, we annotated each nucleotide position with the genome-wide frequency of the 18 bp oligo starting at that position. These frequencies formed landscapes consisting of high- and low-frequency zones. Low-frequency zones contained occasional high-frequency spikes; these may represent footprints of RIM2 transposon activity. BLASTn searches of high-frequency non-SSR (simple sequence repeat) 18 bp oligos returned few sequences from species other than rice. These results demonstrate that, in rice, words are not randomly used between different regions within the same genome, and indicate that words that are frequently repeated within the rice genome tend to be unique to rice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".